MultiQC Report

General Statistics

Showing ¹²³/₁₂₃ rows and ²⁶/₄₆ columns.

Sample Name	% rRNA	dupInt	Duplication	5'-3' bias	M Aligned	Exonic	Intronic	Intergenic	Overlapping Exon	Proper Pairs	Error rate	Non-primary	Reads mapped	% Mapped	% Proper pairs	% MapQ 0 reads	Total seqs	Mean insert	Reads	Reads mapped	% Reads mapped	Total reads	Aligned	Aligned	Uniq aligned	Uniq aligned	Multimapped	Dups	GC	Avg len	Median len	Failed	Seqs	% Duplication	% > Q30	Mb Q30 bases	Reads After Filtering	GC content	% PF	% Adapter	Dups	GC	Avg len	Median len	Failed	Seqs
ERR5974709	0.0	0.2	55.5%	1.21	61.2M	91.9M	12.3M	2.9M	3.4M	35.8%	0.35%	21.7M	122.4M	100.0%	100.0%	1.5%	122.4M	1001.4bp	144.1M	144.1M	100.0%	64.0M	61.2M	95.6%	56.6M	88.4%	4.6M							34.1%	93.1%	15721.7Mb	128.1M	50.4%	98.9%	1.7%
ERR5974709_1																												69.7%	50.0%	133bp	147bp	27%	64.8M								70.0%	50.0%	132bp	142bp	27%	64.0M
ERR5974709_2																												67.3%	50.0%	133bp	147bp	18%	64.8M								68.0%	50.0%	132bp	142bp	18%	64.0M
ERR5974710	0.0	0.2	44.3%	1.22	43.4M	60.3M	12.1M	3.5M	2.4M	44.7%	0.41%	15.2M	86.7M	100.0%	100.0%	1.3%	86.7M	1109.7bp	102.0M	102.0M	100.0%	45.6M	43.4M	95.0%	39.8M	87.1%	3.6M							26.0%	93.3%	11096.8Mb	91.3M	51.7%	98.9%	1.7%
ERR5974710_1																												61.6%	51.0%	131bp	142bp	27%	46.2M								61.9%	51.0%	130bp	142bp	27%	45.6M
ERR5974710_2																												60.0%	51.0%	131bp	142bp	27%	46.2M								60.6%	51.0%	130bp	142bp	27%	45.6M
ERR5974711	0.0	0.2	52.4%	1.19	59.4M	88.4M	11.8M	3.2M	3.2M	36.1%	0.33%	28.5M	118.8M	100.0%	100.0%	2.3%	118.8M	1037.1bp	147.3M	147.3M	100.0%	62.4M	59.4M	95.2%	54.2M	86.9%	5.2M							33.6%	94.1%	15163.1Mb	124.8M	51.8%	99.1%	1.5%
ERR5974711_1																												68.1%	51.0%	130bp	137bp	27%	63.0M								68.3%	51.0%	129bp	137bp	27%	62.4M
ERR5974711_2																												67.5%	51.0%	130bp	137bp	27%	63.0M								68.0%	51.0%	129bp	137bp	27%	62.4M
ERR5974712	0.0	0.2	48.3%	1.20	57.0M	84.5M	12.5M	3.6M	3.4M	42.0%	0.35%	18.6M	113.9M	100.0%	100.0%	1.3%	113.9M	995.7bp	132.6M	132.6M	100.0%	59.7M	57.0M	95.4%	52.9M	88.5%	4.1M							27.6%	93.5%	13990.6Mb	119.5M	51.6%	98.8%	1.9%
ERR5974712_1																												64.4%	51.0%	126bp	137bp	18%	60.5M								64.7%	51.0%	125bp	132bp	18%	59.7M
ERR5974712_2																												62.9%	51.0%	126bp	137bp	18%	60.5M								63.5%	51.0%	126bp	132bp	18%	59.7M
ERR5974713	0.0	0.1	41.5%	1.25	43.7M	63.7M	10.7M	3.0M	2.5M	48.3%	0.33%	13.0M	87.4M	100.0%	100.0%	1.1%	87.4M	968.7bp	100.3M	100.3M	100.0%	45.5M	43.7M	96.1%	40.7M	89.6%	2.9M							24.1%	93.4%	11213.8Mb	90.9M	51.2%	98.8%	1.7%
ERR5974713_1																												60.0%	51.0%	133bp	147bp	18%	46.0M								60.3%	51.0%	132bp	147bp	18%	45.5M
ERR5974713_2																												58.6%	51.0%	133bp	147bp	18%	46.0M								59.1%	51.0%	132bp	147bp	18%	45.5M
ERR5974714	0.0	0.1	44.6%	1.23	40.3M	59.9M	9.3M	2.2M	2.3M	45.1%	0.32%	13.6M	80.7M	100.0%	100.0%	1.4%	80.7M	872.5bp	94.3M	94.3M	100.0%	42.0M	40.3M	96.0%	37.6M	89.5%	2.7M							27.1%	93.2%	10147.9Mb	84.1M	50.0%	98.8%	1.7%
ERR5974714_1																												62.5%	49.0%	131bp	142bp	18%	42.5M								62.8%	49.0%	130bp	142bp	18%	42.0M
ERR5974714_2																												60.9%	50.0%	131bp	142bp	18%	42.5M								61.5%	50.0%	130bp	142bp	18%	42.0M
ERR5974715	0.0	0.2	50.6%	1.13	58.4M	87.2M	11.5M	2.9M	3.3M	37.1%	0.40%	29.2M	116.8M	100.0%	100.0%	2.5%	116.8M	1146.7bp	146.1M	146.1M	100.0%	61.3M	58.4M	95.3%	53.3M	86.9%	5.2M							30.8%	93.5%	15039.4Mb	122.6M	51.9%	99.0%	1.8%
ERR5974715_1																												66.5%	51.0%	132bp	147bp	27%	61.9M								66.8%	51.0%	131bp	142bp	27%	61.3M
ERR5974715_2																												64.6%	51.0%	132bp	147bp	27%	61.9M								65.2%	51.0%	131bp	142bp	27%	61.3M
ERR5974716	0.0	0.2	49.1%	1.19	47.8M	72.3M	9.3M	2.5M	2.7M	40.8%	0.32%	17.5M	95.6M	100.0%	100.0%	1.6%	95.6M	992.5bp	113.1M	113.1M	100.0%	50.1M	47.8M	95.4%	44.3M	88.5%	3.5M							31.0%	93.7%	11956.7Mb	100.1M	51.1%	99.0%	1.7%
ERR5974716_1																												65.1%	51.0%	128bp	137bp	18%	50.6M								65.3%	51.0%	128bp	137bp	18%	50.1M
ERR5974716_2																												63.9%	51.0%	128bp	137bp	18%	50.6M								64.4%	51.0%	128bp	137bp	18%	50.1M
ERR5974717	0.0	0.2	54.0%	1.17	43.8M	67.6M	7.5M	1.6M	2.4M	35.0%	0.31%	21.2M	87.7M	100.0%	100.0%	2.4%	87.7M	965.9bp	108.9M	108.9M	100.0%	45.8M	43.8M	95.7%	40.3M	88.0%	3.5M							34.0%	93.1%	10832.3Mb	91.6M	51.0%	98.8%	2.0%
ERR5974717_1																												68.4%	50.0%	128bp	142bp	18%	46.3M								68.6%	50.0%	127bp	137bp	18%	45.8M
ERR5974717_2																												66.1%	51.0%	128bp	142bp	18%	46.3M								66.8%	51.0%	127bp	137bp	18%	45.8M
ERR5974718	0.0	0.1	57.1%	1.16	50.3M	78.8M	7.8M	1.5M	2.5M	32.9%	0.32%	24.1M	100.6M	100.0%	100.0%	2.4%	100.6M	996.4bp	124.7M	124.7M	100.0%	52.4M	50.3M	96.1%	46.1M	88.0%	4.2M							38.2%	93.3%	12710.0Mb	104.7M	50.7%	99.1%	2.1%
ERR5974718_1																												71.6%	50.0%	131bp	142bp	18%	52.9M								71.9%	50.0%	130bp	142bp	18%	52.4M
ERR5974718_2																												69.7%	50.0%	131bp	142bp	18%	52.9M								70.3%	50.0%	130bp	142bp	18%	52.4M
ERR5974719	0.0	0.2	51.4%	1.17	57.3M	87.5M	11.0M	2.6M	3.2M	38.6%	0.32%	22.2M	114.5M	100.0%	100.0%	1.8%	114.5M	1010.4bp	136.7M	136.7M	100.0%	59.7M	57.3M	95.9%	53.0M	88.8%	4.2M							31.4%	93.3%	14503.5Mb	119.4M	51.2%	99.0%	1.7%
ERR5974719_1																												66.6%	51.0%	131bp	142bp	18%	60.3M								66.8%	51.0%	130bp	137bp	18%	59.7M
ERR5974719_2																												64.5%	51.0%	131bp	142bp	18%	60.3M								65.1%	51.0%	130bp	137bp	18%	59.7M
ERR5974720	0.0	0.2	53.3%	1.19	56.8M	86.3M	10.9M	2.7M	3.3M	37.2%	0.37%	21.6M	113.6M	100.0%	100.0%	1.7%	113.6M	1023.5bp	135.1M	135.1M	100.0%	59.7M	56.8M	95.1%	52.6M	88.0%	4.2M							31.1%	92.7%	14526.1Mb	119.4M	51.0%	98.8%	1.8%
ERR5974720_1																												68.1%	50.0%	132bp	147bp	18%	60.4M								68.4%	50.0%	131bp	142bp	18%	59.7M
ERR5974720_2																												64.9%	51.0%	132bp	147bp	18%	60.4M								65.6%	50.0%	131bp	142bp	18%	59.7M
ERR5974721	0.0	0.2	54.4%	1.15	58.6M	88.6M	10.2M	2.9M	3.3M	35.6%	0.32%	24.5M	117.2M	100.0%	100.0%	1.8%	117.2M	1055.1bp	141.8M	141.8M	100.0%	61.6M	58.6M	95.2%	53.8M	87.3%	4.8M							35.3%	93.8%	14366.4Mb	123.1M	51.1%	99.0%	1.8%
ERR5974721_1																												69.7%	51.0%	125bp	132bp	27%	62.2M								69.9%	51.0%	125bp	132bp	27%	61.6M
ERR5974721_2																												68.6%	51.0%	125bp	132bp	27%	62.2M								69.2%	51.0%	125bp	132bp	27%	61.6M
ERR5974722	0.0	0.2	45.2%	1.18	59.5M	86.2M	13.9M	3.7M	3.5M	41.4%	0.37%	29.6M	119.0M	100.0%	100.0%	2.6%	119.0M	1066.1bp	148.5M	148.5M	100.0%	62.7M	59.5M	94.8%	54.6M	87.0%	4.9M							26.5%	93.3%	15181.7Mb	125.5M	52.3%	98.7%	1.8%
ERR5974722_1																												62.5%	52.0%	130bp	142bp	27%	63.5M								62.7%	52.0%	130bp	137bp	27%	62.7M
ERR5974722_2																												60.3%	52.0%	130bp	142bp	27%	63.5M								60.9%	52.0%	130bp	137bp	27%	62.7M
ERR5974723	0.0	0.2	51.6%	1.23	57.7M	86.5M	11.9M	2.8M	3.2M	38.3%	0.38%	22.3M	115.4M	100.0%	100.0%	1.7%	115.4M	965.8bp	137.7M	137.7M	100.0%	60.6M	57.7M	95.2%	53.4M	88.0%	4.4M							31.8%	93.5%	14216.7Mb	121.3M	51.6%	98.9%	1.7%
ERR5974723_1																												67.1%	51.0%	126bp	137bp	18%	61.3M								67.4%	51.0%	126bp	132bp	18%	60.6M
ERR5974723_2																												64.9%	51.0%	126bp	137bp	18%	61.3M								65.6%	51.0%	126bp	132bp	18%	60.6M
ERR5974724	0.0	1.1	79.4%	1.21	58.7M	87.4M	11.0M	2.2M	3.1M	14.3%	0.31%	39.2M	117.4M	100.0%	100.0%	3.9%	117.4M	941.3bp	156.6M	156.6M	100.0%	61.4M	58.7M	95.6%	53.2M	86.6%	5.5M							53.2%	93.5%	14844.8Mb	122.8M	49.8%	98.9%	1.8%
ERR5974724_1																												79.3%	49.0%	130bp	142bp	27%	62.1M								79.6%	49.0%	129bp	137bp	27%	61.4M
ERR5974724_2																												77.9%	49.0%	130bp	142bp	27%	62.1M								78.6%	49.0%	129bp	137bp	27%	61.4M
ERR5974725	0.0	0.2	47.1%	1.13	58.9M	88.3M	12.6M	2.9M	3.5M	41.8%	0.31%	23.3M	117.7M	100.0%	100.0%	1.8%	117.7M	1016.2bp	141.0M	141.0M	100.0%	61.2M	58.9M	96.1%	54.5M	89.0%	4.3M							29.0%	93.5%	14652.7Mb	122.4M	51.7%	99.0%	1.6%
ERR5974725_1																												63.6%	51.0%	129bp	137bp	18%	61.8M								63.9%	51.0%	128bp	137bp	18%	61.2M
ERR5974725_2																												61.7%	51.0%	129bp	137bp	18%	61.8M								62.3%	51.0%	128bp	137bp	18%	61.2M
ERR5974726	0.0	0.2	40.7%	1.17	46.5M	69.2M	11.6M	2.3M	2.9M	48.7%	0.36%	14.9M	92.9M	100.0%	100.0%	1.4%	92.9M	1024.6bp	107.8M	107.8M	100.0%	48.0M	46.5M	96.7%	43.5M	90.5%	3.0M							22.5%	93.1%	11556.3Mb	96.1M	50.8%	99.0%	1.7%
ERR5974726_1																												57.0%	50.0%	130bp	142bp	18%	48.5M								57.2%	50.0%	129bp	137bp	18%	48.0M
ERR5974726_2																												54.7%	50.0%	130bp	142bp	18%	48.5M								55.2%	50.0%	129bp	137bp	18%	48.0M
ERR5974727	0.0	0.2	43.4%	1.16	59.1M	89.0M	13.6M	2.7M	3.6M	45.7%	0.31%	20.8M	118.2M	100.0%	100.0%	1.6%	118.2M	1110.0bp	139.0M	139.0M	100.0%	61.7M	59.1M	95.8%	55.1M	89.3%	4.0M							25.9%	93.4%	15028.0Mb	123.4M	51.7%	98.9%	1.8%
ERR5974727_1																												60.9%	51.0%	131bp	142bp	18%	62.4M								61.1%	51.0%	131bp	142bp	18%	61.7M
ERR5974727_2																												58.7%	51.0%	131bp	142bp	18%	62.4M								59.2%	51.0%	131bp	142bp	18%	61.7M
ERR5974728	0.0	0.1	42.2%	1.14	40.3M	61.1M	8.8M	1.5M	2.3M	46.8%	0.34%	14.1M	80.6M	100.0%	100.0%	1.5%	80.6M	1030.5bp	94.7M	94.7M	100.0%	41.9M	40.3M	96.3%	37.6M	89.8%	2.7M							26.7%	93.4%	10063.2Mb	83.7M	50.9%	99.0%	1.7%
ERR5974728_1																												59.8%	50.0%	130bp	142bp	18%	42.3M								60.0%	50.0%	129bp	137bp	18%	41.9M
ERR5974728_2																												58.0%	50.0%	130bp	142bp	18%	42.3M								58.5%	50.0%	129bp	137bp	18%	41.9M
ERR5974729	0.0	0.1	52.2%	1.12	57.4M	84.5M	11.7M	2.7M	3.3M	36.0%	0.34%	28.8M	114.9M	100.0%	100.0%	2.1%	114.9M	1160.1bp	143.6M	143.6M	100.0%	60.2M	57.4M	95.3%	51.9M	86.1%	5.6M							33.7%	93.3%	14747.2Mb	120.5M	51.0%	98.9%	1.9%
ERR5974729_1																												68.1%	50.0%	132bp	147bp	27%	60.9M								68.4%	50.0%	131bp	142bp	27%	60.2M
ERR5974729_2																												66.2%	51.0%	132bp	147bp	27%	60.9M								66.8%	50.0%	131bp	142bp	27%	60.2M
ERR5974730	0.0	0.2	51.6%	1.16	57.0M	84.5M	13.0M	2.4M	3.2M	36.5%	0.33%	28.7M	114.1M	100.0%	100.0%	2.6%	114.1M	1029.6bp	142.7M	142.7M	100.0%	59.7M	57.0M	95.5%	52.3M	87.5%	4.8M							31.6%	93.1%	14485.1Mb	119.5M	50.7%	98.9%	1.8%
ERR5974730_1																												65.5%	50.0%	131bp	142bp	18%	60.4M								65.8%	50.0%	130bp	142bp	18%	59.7M
ERR5974730_2																												63.1%	50.0%	131bp	142bp	18%	60.4M								63.7%	50.0%	130bp	142bp	18%	59.7M
ERR5974731	0.0	0.1	47.3%	1.15	45.7M	68.8M	9.5M	1.9M	2.7M	40.2%	0.29%	21.7M	91.4M	100.0%	100.0%	2.4%	91.4M	979.8bp	113.1M	113.1M	100.0%	47.5M	45.7M	96.2%	42.1M	88.6%	3.6M							30.2%	93.5%	11382.5Mb	95.0M	51.2%	99.1%	1.8%
ERR5974731_1																												62.9%	51.0%	129bp	137bp	18%	47.9M								63.1%	51.0%	128bp	137bp	18%	47.5M
ERR5974731_2																												61.3%	51.0%	129bp	137bp	18%	47.9M								61.8%	51.0%	128bp	137bp	18%	47.5M
ERR5974732	0.0	0.2	48.6%	1.16	62.9M	90.4M	16.0M	3.6M	3.8M	39.6%	0.36%	28.5M	125.9M	100.0%	100.0%	2.2%	125.9M	1100.2bp	154.4M	154.4M	100.0%	66.3M	62.9M	95.0%	57.7M	87.1%	5.2M							29.5%	93.4%	16384.8Mb	132.5M	51.6%	99.1%	1.4%
ERR5974732_1																												63.2%	51.0%	133bp	147bp	27%	66.9M								63.4%	51.0%	133bp	142bp	27%	66.3M
ERR5974732_2																												61.0%	51.0%	133bp	147bp	27%	66.9M								61.5%	51.0%	133bp	142bp	27%	66.3M
ERR5974733	0.0	0.2	56.2%	1.18	59.7M	88.9M	12.4M	2.4M	3.6M	33.6%	0.31%	27.7M	119.3M	100.0%	100.0%	2.2%	119.3M	1011.7bp	147.1M	147.1M	100.0%	62.2M	59.7M	96.0%	54.7M	88.0%	5.0M							36.1%	93.3%	15118.0Mb	124.3M	50.6%	99.0%	1.9%
ERR5974733_1																												68.7%	50.0%	131bp	142bp	18%	62.8M								69.0%	50.0%	130bp	137bp	18%	62.2M
ERR5974733_2																												66.8%	50.0%	131bp	142bp	18%	62.8M								67.5%	50.0%	130bp	137bp	18%	62.2M
ERR5974734	0.0	0.1	45.8%	1.17	46.2M	69.7M	9.3M	1.9M	2.6M	41.9%	0.34%	20.7M	92.5M	100.0%	100.0%	2.0%	92.5M	1011.5bp	113.2M	113.2M	100.0%	48.3M	46.2M	95.7%	42.5M	87.8%	3.8M							28.5%	93.6%	11742.2Mb	96.7M	50.8%	99.0%	2.3%
ERR5974734_1																												63.4%	50.0%	131bp	142bp	27%	48.8M								63.7%	50.0%	130bp	142bp	27%	48.3M
ERR5974734_2																												61.9%	50.0%	131bp	142bp	27%	48.8M								62.4%	50.0%	130bp	142bp	27%	48.3M
ERR5974735	0.0	0.1	47.5%	1.14	56.8M	83.9M	12.9M	2.8M	3.4M	40.0%	0.33%	26.7M	113.6M	100.0%	100.0%	2.2%	113.6M	1055.5bp	140.3M	140.3M	100.0%	59.6M	56.8M	95.3%	52.0M	87.2%	4.8M							29.4%	93.6%	14446.4Mb	119.2M	52.4%	99.1%	1.8%
ERR5974735_1																												64.1%	52.0%	130bp	142bp	27%	60.2M								64.3%	52.0%	130bp	137bp	27%	59.6M
ERR5974735_2																												62.8%	52.0%	130bp	142bp	27%	60.2M								63.3%	52.0%	130bp	137bp	27%	59.6M
ERR5974736	0.0	0.2	42.3%	1.18	63.9M	94.7M	15.5M	3.2M	3.9M	47.0%	0.31%	21.1M	127.8M	100.0%	100.0%	1.4%	127.8M	974.4bp	148.9M	148.9M	100.0%	66.3M	63.9M	96.4%	59.6M	90.0%	4.3M							26.2%	93.7%	15838.8Mb	132.5M	51.6%	99.1%	1.6%
ERR5974736_1																												60.6%	51.0%	128bp	137bp	18%	66.9M								60.9%	51.0%	128bp	137bp	18%	66.3M
ERR5974736_2																												59.3%	51.0%	128bp	137bp	18%	66.9M								59.8%	51.0%	128bp	137bp	18%	66.3M
ERR5974737	0.0	0.2	47.9%	1.20	43.2M	63.1M	8.1M	1.6M	2.5M	32.5%	0.36%	42.1M	86.4M	100.0%	100.0%	6.0%	86.4M	1071.5bp	128.5M	128.5M	100.0%	45.2M	43.2M	95.7%	38.4M	85.0%	4.8M							27.2%	93.3%	10947.6Mb	90.3M	51.8%	98.7%	1.9%
ERR5974737_1																												64.5%	51.0%	131bp	147bp	18%	45.8M								64.7%	51.0%	130bp	142bp	18%	45.2M
ERR5974737_2																												62.5%	51.0%	131bp	147bp	18%	45.8M								63.1%	51.0%	130bp	142bp	18%	45.2M
ERR5974738	0.0	0.1	46.8%	1.15	55.7M	84.5M	11.2M	2.3M	3.0M	41.1%	0.29%	25.2M	111.5M	100.0%	100.0%	2.3%	111.5M	963.1bp	136.6M	136.6M	100.0%	57.9M	55.7M	96.2%	51.5M	89.0%	4.2M							30.2%	93.6%	13736.9Mb	115.8M	51.1%	99.0%	1.8%
ERR5974738_1																												63.7%	51.0%	128bp	137bp	18%	58.5M								64.0%	51.0%	127bp	132bp	18%	57.9M
ERR5974738_2																												62.1%	51.0%	128bp	137bp	18%	58.5M								62.7%	51.0%	127bp	132bp	18%	57.9M
ERR5974739	0.0	0.1	46.0%	1.15	58.0M	83.6M	14.4M	2.7M	3.6M	40.6%	0.35%	29.5M	116.0M	100.0%	100.0%	2.5%	116.0M	1031.5bp	145.4M	145.4M	100.0%	61.0M	58.0M	95.1%	52.8M	86.7%	5.1M							28.1%	93.2%	14754.1Mb	122.0M	51.8%	98.9%	2.0%
ERR5974739_1																												61.9%	51.0%	131bp	142bp	27%	61.6M								62.2%	51.0%	130bp	137bp	27%	61.0M
ERR5974739_2																												59.6%	51.0%	131bp	142bp	27%	61.6M								60.3%	51.0%	130bp	137bp	27%	61.0M
ERR5974740	0.0	0.2	40.1%	1.15	48.2M	71.5M	11.7M	2.5M	3.1M	47.7%	0.33%	18.2M	96.4M	100.0%	100.0%	1.8%	96.4M	1076.2bp	114.6M	114.6M	100.0%	50.4M	48.2M	95.6%	44.8M	89.0%	3.4M							23.0%	93.2%	12144.6Mb	100.8M	52.5%	98.9%	1.5%
ERR5974740_1																												57.5%	52.0%	130bp	142bp	18%	50.9M								57.8%	52.0%	129bp	142bp	18%	50.4M
ERR5974740_2																												55.3%	52.0%	130bp	142bp	18%	50.9M								55.8%	52.0%	129bp	142bp	18%	50.4M
ERR5974741	0.0	0.5	68.6%	1.18	59.9M	94.9M	6.4M	2.5M	3.5M	23.9%	0.32%	28.3M	119.9M	100.0%	100.0%	2.1%	119.9M	1230.8bp	148.1M	148.1M	100.0%	62.9M	59.9M	95.3%	54.7M	86.9%	5.3M							43.3%	93.4%	15339.3Mb	125.8M	50.3%	98.9%	1.7%
ERR5974741_1																												75.8%	50.0%	131bp	150bp	18%	63.6M								76.2%	50.0%	131bp	147bp	18%	62.9M
ERR5974741_2																												74.1%	50.0%	131bp	150bp	18%	63.6M								74.8%	50.0%	131bp	147bp	27%	62.9M
ERR5974742	0.0	0.2	58.7%	1.16	58.3M	90.7M	7.6M	2.2M	3.1M	31.1%	0.34%	28.9M	116.5M	100.0%	100.0%	2.2%	116.5M	1221.6bp	145.5M	145.5M	100.0%	61.5M	58.3M	94.7%	52.7M	85.6%	5.6M							36.2%	92.9%	15173.4Mb	123.0M	51.0%	98.9%	1.9%
ERR5974742_1																												72.6%	50.0%	134bp	150bp	27%	62.2M								72.9%	50.0%	133bp	150bp	27%	61.5M
ERR5974742_2																												69.6%	51.0%	134bp	150bp	27%	62.2M								70.4%	51.0%	133bp	150bp	27%	61.5M
ERR5974743	0.0	0.4	62.6%	1.15	36.8M	58.8M	3.3M	1.4M	2.3M	26.7%	0.34%	21.9M	73.6M	100.0%	100.0%	3.3%	73.6M	1246.3bp	95.6M	95.6M	100.0%	38.5M	36.8M	95.7%	33.4M	86.9%	3.4M							37.7%	93.0%	9598.2Mb	76.9M	50.2%	98.7%	1.3%
ERR5974743_1																												74.5%	50.0%	135bp	150bp	18%	39.0M								74.8%	50.0%	134bp	150bp	18%	38.5M
ERR5974743_2																												71.9%	50.0%	135bp	150bp	18%	39.0M								72.7%	50.0%	134bp	150bp	18%	38.5M
ERR5974744	0.0	0.3	64.1%	1.15	39.5M	62.8M	3.1M	1.3M	2.6M	26.9%	0.32%	19.6M	78.9M	100.0%	100.0%	2.3%	78.9M	1362.5bp	98.5M	98.5M	100.0%	41.0M	39.5M	96.2%	35.8M	87.2%	3.7M							40.3%	93.3%	10295.2Mb	82.1M	49.3%	99.1%	1.4%
ERR5974744_1																												76.8%	49.0%	135bp	150bp	18%	41.4M								77.0%	49.0%	135bp	150bp	18%	41.0M
ERR5974744_2																												74.8%	49.0%	135bp	150bp	18%	41.4M								75.4%	49.0%	135bp	150bp	18%	41.0M
ERR5974745	0.0	0.4	66.2%	1.12	48.5M	78.6M	3.6M	1.8M	2.8M	25.6%	0.33%	23.1M	97.1M	100.0%	100.0%	2.1%	97.1M	1262.7bp	120.2M	120.2M	100.0%	50.7M	48.5M	95.8%	44.2M	87.2%	4.4M							41.6%	93.5%	12555.4Mb	101.3M	49.9%	99.1%	1.5%
ERR5974745_1																												76.7%	49.0%	134bp	150bp	18%	51.1M								76.9%	49.0%	133bp	150bp	18%	50.7M
ERR5974745_2																												75.2%	49.0%	134bp	150bp	18%	51.1M								75.7%	49.0%	133bp	150bp	18%	50.7M
ERR5974746	0.0	0.2	52.0%	1.18	61.2M	96.0M	8.8M	2.7M	3.5M	37.9%	0.34%	24.4M	122.5M	100.0%	100.0%	1.8%	122.5M	1212.2bp	146.9M	146.9M	100.0%	63.8M	61.2M	95.9%	56.5M	88.6%	4.7M							30.3%	92.6%	15164.8Mb	127.7M	50.7%	98.6%	2.1%
ERR5974746_1																												67.6%	50.0%	129bp	142bp	18%	64.7M								67.9%	50.0%	128bp	137bp	18%	63.8M
ERR5974746_2																												63.4%	50.0%	129bp	142bp	18%	64.7M								64.2%	50.0%	129bp	137bp	18%	63.8M
ERR5974747	0.0	0.9	73.9%	1.27	43.6M	69.3M	6.8M	1.3M	2.4M	21.5%	0.34%	12.7M	87.2M	100.0%	100.0%	1.3%	87.2M	1007.5bp	99.9M	99.9M	100.0%	44.8M	43.6M	97.3%	41.1M	91.8%	2.5M							45.6%	93.7%	10600.4Mb	89.6M	49.6%	98.7%	2.1%
ERR5974747_1																												75.0%	49.0%	127bp	137bp	18%	45.4M								75.3%	49.0%	126bp	137bp	18%	44.8M
ERR5974747_2																												73.3%	49.0%	127bp	137bp	18%	45.4M								74.0%	49.0%	126bp	137bp	18%	44.8M
ERR5974748	0.0	0.9	78.9%	1.27	58.2M	92.2M	6.5M	2.1M	3.8M	15.5%	0.33%	29.3M	116.4M	100.0%	100.0%	2.7%	116.4M	1231.2bp	145.7M	145.7M	100.0%	60.4M	58.2M	96.3%	53.4M	88.4%	4.8M							49.5%	92.5%	14868.5Mb	120.9M	49.8%	97.9%	1.9%
ERR5974748_1																												82.7%	49.0%	134bp	150bp	18%	61.8M								83.1%	49.0%	133bp	150bp	18%	60.4M
ERR5974748_2																												78.4%	49.0%	134bp	150bp	18%	61.8M								79.5%	49.0%	133bp	150bp	18%	60.4M
ERR5974749	0.0	0.5	70.6%	1.21	57.9M	93.7M	4.1M	1.7M	2.9M	20.7%	0.31%	36.9M	115.8M	100.0%	100.0%	3.5%	115.8M	1204.1bp	152.7M	152.7M	100.0%	60.5M	57.9M	95.7%	52.3M	86.4%	5.6M							46.0%	93.7%	14939.6Mb	121.0M	50.9%	99.1%	1.7%
ERR5974749_1																												79.1%	50.0%	133bp	150bp	18%	61.1M								79.4%	50.0%	132bp	147bp	18%	60.5M
ERR5974749_2																												77.7%	50.0%	133bp	150bp	18%	61.1M								78.3%	50.0%	132bp	147bp	18%	60.5M

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: general_stats_table_table

Sort	Group	Column	Description	ID	Scale
\|\|	Custom content: Biotype Counts	% rRNA	% reads overlapping rRNA features	`custom_content_biotype_counts-percent_rRNA`
\|\|	Custom content: DupRadar	dupInt	Intercept value from DupRadar	`custom_content_dupradar-dupRadar_intercept`
\|\|	Picard: Mark Duplicates	Duplication	Mark Duplicates - Percent Duplication	`picard_mark_duplicates-PERCENT_DUPLICATION`
\|\|	QualiMap: RNASeq	5'-3' bias	5'-3' bias	`qualimap_rnaseq-5_3_bias`
\|\|	QualiMap: RNASeq	M Aligned	Reads Aligned (millions)	`qualimap_rnaseq-reads_aligned`	read_count
\|\|	QualiMap: RNASeq	Exonic	Reads aligned to exonic regions	`qualimap_rnaseq-reads_aligned_exonic`	read_count
\|\|	QualiMap: RNASeq	Intronic	Reads aligned to intronic regions	`qualimap_rnaseq-reads_aligned_intronic`	read_count
\|\|	QualiMap: RNASeq	Intergenic	Reads aligned to intergenic regions	`qualimap_rnaseq-reads_aligned_intergenic`	read_count
\|\|	QualiMap: RNASeq	Overlapping Exon	Reads aligned to overlapping exon regions	`qualimap_rnaseq-reads_aligned_overlapping_exon`	read_count
\|\|	RSeQC: Bam Stat	Proper Pairs	% Reads mapped in proper pairs	`rseqc_bam_stat-proper_pairs_percent`
\|\|	Samtools: stats	Error rate	Error rate: mismatches (NM) / bases mapped (CIGAR)	`samtools_stats-error_rate`
\|\|	Samtools: stats	Non-primary	Non-primary alignments (millions)	`samtools_stats-non_primary_alignments`	read_count
\|\|	Samtools: stats	Reads mapped	Reads mapped in the bam file (millions)	`samtools_stats-reads_mapped`	read_count
\|\|	Samtools: stats	% Mapped	% Mapped reads	`samtools_stats-reads_mapped_percent`
\|\|	Samtools: stats	% Proper pairs	% Properly paired reads	`samtools_stats-reads_properly_paired_percent`
\|\|	Samtools: stats	% MapQ 0 reads	% of reads that are ambiguously placed (MapQ=0)	`samtools_stats-reads_MQ0_percent`
\|\|	Samtools: stats	Total seqs	Total sequences in the bam file (millions)	`samtools_stats-raw_total_sequences`	read_count
\|\|	Samtools: stats	Mean insert	Average insert size	`samtools_stats-insert_size_average`
\|\|	Samtools: flagstat	Reads	Total reads in the bam file (millions)	`samtools_flagstat-flagstat_total`	read_count
\|\|	Samtools: flagstat	Reads mapped	Reads mapped in the bam file (millions)	`samtools_flagstat-mapped_passed`	read_count
\|\|	Samtools: flagstat	% Reads mapped	% Reads mapped in the bam file	`samtools_flagstat-mapped_passed_pct`
\|\|	STAR	Total reads	Number of input reads	`star-total_reads`	read_count
\|\|	STAR	Aligned	Mapped reads	`star-mapped`	read_count
\|\|	STAR	Aligned	% Mapped reads	`star-mapped_percent`
\|\|	STAR	Uniq aligned	Uniquely mapped reads	`star-uniquely_mapped`	read_count
\|\|	STAR	Uniq aligned	% Uniquely mapped reads	`star-uniquely_mapped_percent`
\|\|	STAR	Multimapped	Multiple mapped reads	`star-multimapped`	read_count
\|\|	FastQC (raw)	Dups	% duplicate reads	`fastqc_raw-percent_duplicates`
\|\|	FastQC (raw)	GC	Average % GC content	`fastqc_raw-percent_gc`
\|\|	FastQC (raw)	Avg len	Average read length	`fastqc_raw-avg_sequence_length`
\|\|	FastQC (raw)	Median len	Median read length	`fastqc_raw-median_sequence_length`
\|\|	FastQC (raw)	Failed	Percentage of modules failed in FastQC report (includes those not plotted here)	`fastqc_raw-percent_fails`
\|\|	FastQC (raw)	Seqs	Total sequences (millions)	`fastqc_raw-total_sequences`	read_count
\|\|	fastp	% Duplication	Duplication rate before filtering	`fastp-pct_duplication`
\|\|	fastp	% > Q30	Percentage of reads > Q30 after filtering	`fastp-after_filtering_q30_rate`
\|\|	fastp	Mb Q30 bases	Bases > Q30 after filtering (millions)	`fastp-after_filtering_q30_bases`	base_count
\|\|	fastp	Reads After Filtering	Total reads after filtering (millions)	`fastp-filtering_result_passed_filter_reads`	read_count
\|\|	fastp	GC content	GC content after filtering	`fastp-after_filtering_gc_content`
\|\|	fastp	% PF	Percent reads passing filter	`fastp-pct_surviving`
\|\|	fastp	% Adapter	Percentage adapter-trimmed reads	`fastp-pct_adapter`
\|\|	FastQC (trimmed)	Dups	% duplicate reads	`fastqc_trimmed-percent_duplicates`
\|\|	FastQC (trimmed)	GC	Average % GC content	`fastqc_trimmed-percent_gc`
\|\|	FastQC (trimmed)	Avg len	Average read length	`fastqc_trimmed-avg_sequence_length`
\|\|	FastQC (trimmed)	Median len	Median read length	`fastqc_trimmed-median_sequence_length`
\|\|	FastQC (trimmed)	Failed	Percentage of modules failed in FastQC report (includes those not plotted here)	`fastqc_trimmed-percent_fails`
\|\|	FastQC (trimmed)	Seqs	Total sequences (millions)	`fastqc_trimmed-total_sequences`	read_count

Sample status checks

Reports on sample strandedness status, and any failures in trimming or mapping.

Strandedness Checks

The strandedness used for analysis in this workflow can either be provided by the user or automatically inferred by Salmon using a sample of reads. In both cases, strandedness is verified at the end of the workflow using RSeQC's infer_experiment.py on genomic alignments. In this table, a pass indicates a match between the supplied strandedness (or that inferred by Salmon) and RSeQC results. A fail indicates a mismatch or 'undetermined' strandedness. 'Undetermined' strandedness can signal QC issues, including potential genomic DNA contamination.

Note: Rows are duplicated for an 'auto' setting to allow comparison of statistics between inference methods.

Showing ⁸²/₈₂ rows and ⁷/₇ columns.

Sample	Status	Strand inference method	Provided strandedness	Inferred strandedness	Sense (%)	Antisense (%)	Unstranded (%)
ERR5974709	pass	RSeQC	auto	unstranded	44.7	44.5	10.7
ERR5974709	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974710	pass	RSeQC	auto	unstranded	44.1	44.6	11.3
ERR5974710	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974711	pass	RSeQC	auto	unstranded	45.2	45.1	9.7
ERR5974711	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974712	pass	RSeQC	auto	unstranded	42.4	42.3	15.3
ERR5974712	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974713	pass	RSeQC	auto	unstranded	43.8	43.7	12.6
ERR5974713	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974714	pass	RSeQC	auto	unstranded	42.8	42.6	14.6
ERR5974714	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974715	pass	RSeQC	auto	unstranded	44.1	44.3	11.6
ERR5974715	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974716	pass	RSeQC	auto	unstranded	44.5	44.5	11.0
ERR5974716	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974717	pass	RSeQC	auto	unstranded	44.8	44.6	10.5
ERR5974717	pass	Salmon	auto	unstranded	49.6	50.4	0.0
ERR5974718	pass	RSeQC	auto	unstranded	45.5	45.1	9.4
ERR5974718	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974719	pass	RSeQC	auto	unstranded	45.5	45.2	9.4
ERR5974719	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974720	pass	RSeQC	auto	unstranded	45.1	45.0	9.9
ERR5974720	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974721	pass	RSeQC	auto	unstranded	45.3	45.8	8.9
ERR5974721	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974722	pass	RSeQC	auto	unstranded	44.5	44.9	10.6
ERR5974722	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974723	pass	RSeQC	auto	unstranded	36.5	36.7	26.8
ERR5974723	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974724	pass	RSeQC	auto	unstranded	44.8	44.7	10.5
ERR5974724	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974725	pass	RSeQC	auto	unstranded	45.4	44.9	9.7
ERR5974725	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974726	pass	RSeQC	auto	unstranded	36.2	35.9	27.9
ERR5974726	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974727	pass	RSeQC	auto	unstranded	44.4	44.2	11.4
ERR5974727	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974728	pass	RSeQC	auto	unstranded	44.9	44.5	10.6
ERR5974728	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974729	pass	RSeQC	auto	unstranded	45.5	45.3	9.3
ERR5974729	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974730	pass	RSeQC	auto	unstranded	45.4	45.3	9.3
ERR5974730	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974731	pass	RSeQC	auto	unstranded	44.7	44.8	10.4
ERR5974731	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974732	pass	RSeQC	auto	unstranded	44.5	44.2	11.3
ERR5974732	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974733	pass	RSeQC	auto	unstranded	44.5	44.2	11.3
ERR5974733	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974734	pass	RSeQC	auto	unstranded	45.2	45.4	9.4
ERR5974734	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974735	pass	RSeQC	auto	unstranded	45.5	45.4	9.0
ERR5974735	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974736	pass	RSeQC	auto	unstranded	44.7	44.4	11.0
ERR5974736	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974737	pass	RSeQC	auto	unstranded	44.5	45.1	10.3
ERR5974737	pass	Salmon	auto	unstranded	49.9	50.1	0.0
ERR5974738	pass	RSeQC	auto	unstranded	45.3	45.1	9.6
ERR5974738	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974739	pass	RSeQC	auto	unstranded	45.1	45.2	9.7
ERR5974739	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974740	pass	RSeQC	auto	unstranded	45.7	45.6	8.7
ERR5974740	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974741	pass	RSeQC	auto	unstranded	44.4	44.9	10.7
ERR5974741	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974742	pass	RSeQC	auto	unstranded	42.7	42.7	14.6
ERR5974742	pass	Salmon	auto	unstranded	49.6	50.4	0.0
ERR5974743	pass	RSeQC	auto	unstranded	43.7	43.8	12.5
ERR5974743	pass	Salmon	auto	unstranded	49.7	50.3	0.0
ERR5974744	pass	RSeQC	auto	unstranded	44.4	44.5	11.1
ERR5974744	pass	Salmon	auto	unstranded	49.8	50.2	0.0
ERR5974745	pass	RSeQC	auto	unstranded	41.5	41.8	16.7
ERR5974745	pass	Salmon	auto	unstranded	49.6	50.4	0.0
ERR5974746	pass	RSeQC	auto	unstranded	43.5	43.7	12.9
ERR5974746	pass	Salmon	auto	unstranded	49.6	50.4	0.0
ERR5974747	pass	RSeQC	auto	unstranded	43.3	43.3	13.3
ERR5974747	pass	Salmon	auto	unstranded	50.0	50.0	0.0
ERR5974748	pass	RSeQC	auto	unstranded	43.1	43.9	13.1
ERR5974748	pass	Salmon	auto	unstranded	49.9	50.1	0.0
ERR5974749	pass	RSeQC	auto	unstranded	44.2	44.1	11.7
ERR5974749	pass	Salmon	auto	unstranded	49.7	50.3	0.0

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: fail_strand_check_table_table

Sort	Column	Description	ID
\|\|	Status	Pass if the strandedness inferred by RSeQC matches that provided by the user or predicted by Salmon. Fail otherwise.	`samples_strandedness_check-Status`
\|\|	Strand inference method	Tool used to detect strandedness	`samples_strandedness_check-Strand_inference_method`
\|\|	Provided strandedness	User-provided strandedness	`samples_strandedness_check-Provided_strandedness`
\|\|	Inferred strandedness	Interred strandedness	`samples_strandedness_check-Inferred_strandedness`
\|\|	Sense (%)	Sense (%)	`samples_strandedness_check-Sense`
\|\|	Antisense (%)	Antisense (%)	`samples_strandedness_check-Antisense`
\|\|	Unstranded (%)	Unstranded (%)	`samples_strandedness_check-Unstranded`

FastQC (raw)

This section of the report shows FastQC results before adapter trimming.URL: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

Sequence Counts

Sequence counts for each sample. Duplicate read counts are an estimate only.

This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

Created with MultiQC

Sequence Quality Histograms

The mean quality value across each base position in the read.

To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

Taken from the FastQC help:

The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

Created with MultiQC

Per Sequence Quality Scores

The number of reads with average quality scores. Shows if a subset of reads has poor quality.

From the FastQC help:

The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

Created with MultiQC

Per Base Sequence Content

The proportion of each base position for which each of the four normal DNA bases has been called.

To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

To see the data as a line plot, as in the original FastQC graph, click on a sample track.

From the FastQC help:

Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

Click a sample row to see a line plot for that dataset.

Rollover for sample name

Position: -

%T: -

%C: -

%A: -

%G: -

Per Sequence GC Content

The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

From the FastQC help:

This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

Created with MultiQC

Per Base N Content

The percentage of base calls at each position for which an N was called.

From the FastQC help:

If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

Created with MultiQC

Sequence Length Distribution

The distribution of fragment sizes (read lengths) found. See the FastQC help

Created with MultiQC

Sequence Duplication Levels

The relative level of duplication found for every sequence.

From the FastQC Help:

In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (e.g. PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

Created with MultiQC

Overrepresented sequences by sample

The total amount of overrepresented sequences found in each library.

FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

From the FastQC Help:

A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

Created with MultiQC

Top overrepresented sequences

Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

Showing ²⁰/₂₀ rows and ³/₃ columns.

Overrepresented sequence	Reports	Occurrences	% of all reads
CTGGGATGCACCGGCCAGAGGCCATGCTGCTGCTGCTCACGCTTGCCCTC	42	3422852	0.0744%
CGAGAGCCCTGGGATGCACCGGCCAGAGGCCATGCTGCTGCTGCTCACGC	15	1121443	0.0244%
GTCACAGGCGAGAGCCCTGGGATGCACCGGCCAGAGGCCATGCTGCTGCT	7	522771	0.0114%
CAACCATTTACTTTTCCCTGAATGTTAGAAACTACAAAACCACTACCTTG	3	214528	0.0047%
GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG	2	143387	0.0031%
GATCGGAAGAGCACACGTCTGAACTCCAGTCACC	1	137768	0.0030%
GTGATTTCATGGTCGTAGTCTTCAGTGGTGCTGAAATACTTGCCTCCTCC	2	136726	0.0030%
CTTCAGTGGTGCTGAAATACTTGCCTCCTCCAGGGCCATACATCTTCCCT	2	132491	0.0029%
GATCGGAAGAGCACACGTCTGAACTCCAGTCACCT	1	128547	0.0028%
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT	2	118396	0.0026%
CAGGAAGTCACCCTGCAGCCAGGCGAATACATCACAAAAGTCTTTGTCGC	2	115796	0.0025%
GCCACATTCAGTTCTTATCAAAGAAATAACCCAGACTTAATCTTGAATGA	2	106083	0.0023%
CCGTGATCCACAAGGCATTAGAGCATGGGTGGCATGGAGAAATCGTTGTC	2	96362	0.0021%
GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG	1	95868	0.0021%
CGACAATCCAAAAACCTTCTACTGGGACTTTTACACCAACAGAACTGTGC	2	90417	0.0020%
GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG	1	84838	0.0018%
CCCAGTTTCACGTCCCAGGAGTCTCCAAGTTTCACCTGGACACTTTTCAC	1	53098	0.0012%
GCTTAATATAAAATAACCACATTAGTGAACATTATATCTCTTAGAAGAAA	1	45488	0.0010%
GATCGGAAGAGCACACGTCTGAACTCCAGTCACCAA	1	45376	0.0010%
CTAAGATCTATTTAAGATAACCTTTTCTTATATTTTTTACTTAATATTGG	1	41929	0.0009%

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: fastqc_raw_top_overrepresented_sequences_table_table

Sort	Column	Description	ID
\|\|	Reports	Number of FastQC reports where this sequence is founds as overrepresented	`fastqc_raw-samples`
\|\|	Occurrences	Total number of occurrences of the sequence (among the samples where the sequence is overrepresented)	`fastqc_raw-total_count`
\|\|	% of all reads	Total number of occurrences as the percentage of all reads (among samples where the sequence is overrepresented)	`fastqc_raw-total_percent`

Adapter Content

The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

Note that only samples with ≥ 0.1% adapter contamination are shown.

There may be several lines per sample, as one is shown for each adapter detected in the file.

From the FastQC Help:

The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

Created with MultiQC

Status Checks

Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

Created with MultiQC

fastp

All-in-one FASTQ preprocessor (QC, adapters, trimming, filtering, splitting...).URL: https://github.com/OpenGene/fastpDOI: 10.1093/bioinformatics/bty560

Fastp goes through fastq files in a folder and perform a series of quality control and filtering. Quality control and reporting are displayed both before and after filtering, allowing for a clear depiction of the consequences of the filtering process. Notably, the latter can be conducted on a variety of parameters including quality scores, length, as well as the presence of adapters, polyG, or polyX tailing.

Filtered Reads

Filtering statistics of sampled reads.

Created with MultiQC

Insert Sizes

Insert size estimation of sampled reads.

Created with MultiQC

Sequence Quality

Average sequencing quality over each base of all reads.

Created with MultiQC

GC Content

Average GC content over each base of all reads.

Created with MultiQC

N content

Average N content over each base of all reads.

Created with MultiQC

FastQC (trimmed)

This section of the report shows FastQC results after adapter trimming.URL: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

Sequence Counts

Sequence counts for each sample. Duplicate read counts are an estimate only.

This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

Created with MultiQC

Sequence Quality Histograms

The mean quality value across each base position in the read.

To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

Taken from the FastQC help:

The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

Created with MultiQC

Per Sequence Quality Scores

The number of reads with average quality scores. Shows if a subset of reads has poor quality.

From the FastQC help:

The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

Created with MultiQC

Per Base Sequence Content

The proportion of each base position for which each of the four normal DNA bases has been called.

To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

To see the data as a line plot, as in the original FastQC graph, click on a sample track.

From the FastQC help:

Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

Click a sample row to see a line plot for that dataset.

Rollover for sample name

Position: -

%T: -

%C: -

%A: -

%G: -

Per Sequence GC Content

The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

From the FastQC help:

This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

Created with MultiQC

Per Base N Content

The percentage of base calls at each position for which an N was called.

From the FastQC help:

If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

Created with MultiQC

Sequence Length Distribution

The distribution of fragment sizes (read lengths) found. See the FastQC help

Created with MultiQC

Sequence Duplication Levels

The relative level of duplication found for every sequence.

From the FastQC Help:

In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (e.g. PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

Created with MultiQC

Overrepresented sequences by sample

The total amount of overrepresented sequences found in each library.

FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

From the FastQC Help:

A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

Created with MultiQC

Top overrepresented sequences

Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

Showing ¹⁴/₁₄ rows and ³/₃ columns.

Overrepresented sequence	Reports	Occurrences	% of all reads
CTGGGATGCACCGGCCAGAGGCCATGCTGCTGCTGCTCACGCTTGCCCTC	43	3465354	0.0761%
CGAGAGCCCTGGGATGCACCGGCCAGAGGCCATGCTGCTGCTGCTCACGC	15	1118659	0.0246%
GTCACAGGCGAGAGCCCTGGGATGCACCGGCCAGAGGCCATGCTGCTGCT	7	521355	0.0115%
CAACCATTTACTTTTCCCTGAATGTTAGAAACTACAAAACCACTACCTTG	3	214186	0.0047%
GTGATTTCATGGTCGTAGTCTTCAGTGGTGCTGAAATACTTGCCTCCTCC	3	198513	0.0044%
CTTCAGTGGTGCTGAAATACTTGCCTCCTCCAGGGCCATACATCTTCCCT	2	132218	0.0029%
CAGGAAGTCACCCTGCAGCCAGGCGAATACATCACAAAAGTCTTTGTCGC	2	115536	0.0025%
GCCACATTCAGTTCTTATCAAAGAAATAACCCAGACTTAATCTTGAATGA	2	105868	0.0023%
CCCAGTTTCACGTCCCAGGAGTCTCCAAGTTTCACCTGGACACTTTTCAC	2	105326	0.0023%
CCGTGATCCACAAGGCATTAGAGCATGGGTGGCATGGAGAAATCGTTGTC	2	96211	0.0021%
CGACAATCCAAAAACCTTCTACTGGGACTTTTACACCAACAGAACTGTGC	2	90211	0.0020%
GCTTAATATAAAATAACCACATTAGTGAACATTATATCTCTTAGAAGAAA	2	86599	0.0019%
GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG	1	62408	0.0014%
CTAAGATCTATTTAAGATAACCTTTTCTTATATTTTTTACTTAATATTGG	1	41861	0.0009%

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: fastqc_trimmed_top_overrepresented_sequences_table_table

Sort	Column	Description	ID
\|\|	Reports	Number of FastQC reports where this sequence is founds as overrepresented	`fastqc_trimmed-samples`
\|\|	Occurrences	Total number of occurrences of the sequence (among the samples where the sequence is overrepresented)	`fastqc_trimmed-total_count`
\|\|	% of all reads	Total number of occurrences as the percentage of all reads (among samples where the sequence is overrepresented)	`fastqc_trimmed-total_percent`

Adapter Content

The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

Note that only samples with ≥ 0.1% adapter contamination are shown.

There may be several lines per sample, as one is shown for each adapter detected in the file.

From the FastQC Help:

The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

Created with MultiQC

Status Checks

Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

Created with MultiQC

DupRadar

DupRadar provides duplication rate quality control for RNA-Seq datasets. Highly expressed genes can be expected to have a lot of duplicate reads, but high numbers of duplicates at low read counts can indicate low library complexity with technical duplication. This plot shows the general linear models - a summary of the gene duplication distributions.URL: bioconductor.org/packages/release/bioc/html/dupRadar.html

Created with MultiQC

Picard

Tools for manipulating high-throughput sequencing data.URL: http://broadinstitute.github.io/picard

Mark Duplicates

Number of reads, categorised by duplication state. Pair counts are doubled - see help text for details.

The table in the Picard metrics file contains some columns referring read pairs and some referring to single reads.

To make the numbers in this plot sum correctly, values referring to pairs are doubled according to the scheme below:

READS_IN_DUPLICATE_PAIRS = 2 * READ_PAIR_DUPLICATES
READS_IN_UNIQUE_PAIRS = 2 * (READ_PAIRS_EXAMINED - READ_PAIR_DUPLICATES)
READS_IN_UNIQUE_UNPAIRED = UNPAIRED_READS_EXAMINED - UNPAIRED_READ_DUPLICATES
READS_IN_DUPLICATE_PAIRS_OPTICAL = 2 * READ_PAIR_OPTICAL_DUPLICATES
READS_IN_DUPLICATE_PAIRS_NONOPTICAL = READS_IN_DUPLICATE_PAIRS - READS_IN_DUPLICATE_PAIRS_OPTICAL
READS_IN_DUPLICATE_UNPAIRED = UNPAIRED_READ_DUPLICATES
READS_UNMAPPED = UNMAPPED_READS

Created with MultiQC

QualiMap

Quality control of alignment data and its derivatives like feature counts.URL: http://qualimap.bioinfo.cipf.esDOI: 10.1093/bioinformatics/btv566; 10.1093/bioinformatics/bts503

Genomic origin of reads

Classification of mapped reads as originating in exonic, intronic or intergenic regions. These can be displayed as either the number or percentage of mapped reads.

There are currently three main approaches to map reads to transcripts in an RNA-seq experiment: mapping reads to a reference genome to identify expressed transcripts that are annotated (and discover those that are unknown), mapping reads to a reference transcriptome, and de novo assembly of transcript sequences (Conesa et al. 2016).

For RNA-seq QC analysis, QualiMap can be used to assess alignments produced by the first of these approaches. For input, it requires a GTF annotation file along with a reference genome, which can be used to reconstruct the exon structure of known transcripts. This allows mapped reads to be grouped by whether they originate in an exonic region (for QualiMap, this may include 5′ and 3′ UTR regions as well as protein-coding exons), an intron, or an intergenic region (see the Qualimap 2 documentation).

The inferred genomic origins of RNA-seq reads are presented here as a bar graph showing either the number or percentage of mapped reads in each read dataset that have been assigned to each type of genomic region. This graph can be used to assess the proportion of useful reads in an RNA-seq experiment. That proportion can be reduced by the presence of intron sequences, especially if depletion of ribosomal RNA was used during sample preparation (Sims et al. 2014). It can also be reduced by off-target transcripts, which are detected in greater numbers at the sequencing depths needed to detect poorly-expressed transcripts (Tarazona et al. 2011).

Created with MultiQC

Gene Coverage Profile

Mean distribution of coverage depth across the length of all mapped transcripts.

There are currently three main approaches to map reads to transcripts in an RNA-seq experiment: mapping reads to a reference genome to identify expressed transcripts that are annotated (and discover those that are unknown), mapping reads to a reference transcriptome, and de novo assembly of transcript sequences (Conesa et al. 2016).

For RNA-seq QC analysis, QualiMap can be used to assess alignments produced by the first of these approaches. For input, it requires a GTF annotation file along with a reference genome, which can be used to reconstruct the exon structure of known transcripts. QualiMap uses this information to calculate the depth of coverage along the length of each annotated transcript. For a set of reads mapped to a transcript, the depth of coverage at a given base position is the number of high-quality reads that map to the transcript at that position (Sims et al. 2014).

QualiMap calculates coverage depth at every base position of each annotated transcript. To enable meaningful comparison between transcripts, base positions are rescaled to relative positions expressed as percentage distance along each transcript (0%, 1%, …, 99%). For the set of transcripts with at least one mapped read, QualiMap plots the cumulative mapped-read depth (y-axis) at each relative transcript position (x-axis). This plot shows the gene coverage profile across all mapped transcripts for each read dataset. It provides a visual way to assess positional biases, such as an accumulation of mapped reads at the 3′ end of transcripts, which may indicate poor RNA quality in the original sample (Conesa et al. 2016).

The Normalised plot is calculated by MultiQC to enable comparison of samples with varying sequencing depth. The cumulative mapped-read depth at each position across the averaged transcript position are divided by the total for that sample across the entire averaged transcript.

Created with MultiQC

RSeQC

Evaluates high throughput RNA-seq data.URL: http://rseqc.sourceforge.netDOI: 10.1093/bioinformatics/bts356

Read Distribution

Read Distribution calculates how mapped reads are distributed over genome features.

Created with MultiQC

Inner Distance

Inner Distance calculates the inner distance (or insert size) between two paired RNA reads. Note that this can be negative if fragments overlap.

Created with MultiQC

Read Duplication

read_duplication.py calculates how many alignment positions have a certain number of exact duplicates. Note - plot truncated at 500 occurrences and binned.

Created with MultiQC

Junction Annotation

Junction annotation compares detected splice junctions to a reference gene model. An RNA read can be spliced 2 or more times, each time is called a splicing event.

Created with MultiQC

Junction Saturation

Junction Saturation counts the number of known splicing junctions that are observed in each dataset. If sequencing depth is sufficient, all (annotated) splice junctions should be rediscovered, resulting in a curve that reaches a plateau. Missing low abundance splice junctions can affect downstream analysis.

Created with MultiQC

Infer experiment

Infer experiment counts the percentage of reads and read pairs that match the strandedness of overlapping transcripts. It can be used to infer whether RNA-seq library preps are stranded (sense or antisense).

Created with MultiQC

Bam Stat

All numbers reported in millions.

Created with MultiQC

Showing ⁴¹/₄₁ rows and ¹⁴/₁₄ columns.

Sample Name	Total records	QC failed	Duplicates	Non primary hit	Unmapped	Unique	Read-1	Read-2	+ve strand	-ve strand	Non-splice reads	Splice reads	Proper pairs	Different chrom
ERR5974709	144.1M	0.0M	67.9M	21.7M	0.0M	51.6M	25.8M	25.8M	25.8M	25.8M	35.0M	16.7M	51.6M	0.0M
ERR5974710	102.0M	0.0M	38.4M	15.2M	0.0M	45.6M	22.8M	22.8M	22.8M	22.8M	31.7M	13.9M	45.6M	0.0M
ERR5974711	147.3M	0.0M	62.3M	28.5M	0.0M	53.2M	26.6M	26.6M	26.6M	26.6M	35.4M	17.7M	53.2M	0.0M
ERR5974712	132.6M	0.0M	55.0M	18.6M	0.0M	55.7M	27.9M	27.9M	27.9M	27.9M	37.8M	17.9M	55.7M	0.0M
ERR5974713	100.3M	0.0M	36.3M	13.0M	0.0M	48.5M	24.2M	24.2M	24.2M	24.2M	33.2M	15.3M	48.5M	0.0M
ERR5974714	94.3M	0.0M	36.0M	13.6M	0.0M	42.5M	21.3M	21.3M	21.3M	21.3M	29.6M	12.9M	42.5M	0.0M
ERR5974715	146.1M	0.0M	59.1M	29.2M	0.0M	54.2M	27.1M	27.1M	27.1M	27.1M	35.3M	18.9M	54.2M	0.0M
ERR5974716	113.1M	0.0M	46.9M	17.5M	0.0M	46.1M	23.1M	23.1M	23.1M	23.1M	30.8M	15.3M	46.1M	0.0M
ERR5974717	108.9M	0.0M	47.3M	21.2M	0.0M	38.1M	19.1M	19.1M	19.1M	19.1M	25.3M	12.8M	38.1M	0.0M
ERR5974718	124.7M	0.0M	57.4M	24.1M	0.0M	41.0M	20.5M	20.5M	20.5M	20.5M	26.7M	14.3M	41.0M	0.0M
ERR5974719	136.7M	0.0M	58.8M	22.2M	0.0M	52.8M	26.4M	26.4M	26.4M	26.4M	34.8M	18.1M	52.8M	0.0M
ERR5974720	135.1M	0.0M	60.5M	21.6M	0.0M	50.2M	25.1M	25.1M	25.1M	25.1M	33.3M	16.9M	50.2M	0.0M
ERR5974721	141.8M	0.0M	63.7M	24.5M	0.0M	50.4M	25.2M	25.2M	25.2M	25.2M	33.3M	17.1M	50.4M	0.0M
ERR5974722	148.5M	0.0M	53.8M	29.6M	0.0M	61.5M	30.7M	30.7M	30.7M	30.7M	41.3M	20.2M	61.5M	0.0M
ERR5974723	137.7M	0.0M	59.6M	22.3M	0.0M	52.8M	26.4M	26.4M	26.4M	26.4M	35.8M	17.0M	52.8M	0.0M
ERR5974724	156.6M	0.0M	93.2M	39.2M	0.0M	22.4M	11.2M	11.2M	11.2M	11.2M	15.2M	7.2M	22.4M	0.0M
ERR5974725	141.0M	0.0M	55.5M	23.3M	0.0M	58.9M	29.5M	29.5M	29.5M	29.5M	39.0M	19.9M	58.9M	0.0M
ERR5974726	107.8M	0.0M	37.8M	14.9M	0.0M	52.4M	26.2M	26.2M	26.2M	26.2M	35.2M	17.3M	52.4M	0.0M
ERR5974727	139.0M	0.0M	51.4M	20.8M	0.0M	63.6M	31.8M	31.8M	31.8M	31.8M	41.5M	22.1M	63.6M	0.0M
ERR5974728	94.7M	0.0M	34.0M	14.1M	0.0M	44.3M	22.2M	22.2M	22.2M	22.2M	29.4M	15.0M	44.3M	0.0M
ERR5974729	143.6M	0.0M	59.9M	28.8M	0.0M	51.7M	25.9M	25.9M	25.9M	25.9M	34.0M	17.8M	51.7M	0.0M
ERR5974730	142.7M	0.0M	58.8M	28.7M	0.0M	52.1M	26.0M	26.0M	26.0M	26.0M	35.5M	16.6M	52.1M	0.0M
ERR5974731	113.1M	0.0M	43.3M	21.7M	0.0M	45.5M	22.7M	22.7M	22.7M	22.7M	30.3M	15.1M	45.5M	0.0M
ERR5974732	154.4M	0.0M	61.1M	28.5M	0.0M	61.1M	30.6M	30.6M	30.6M	30.6M	41.4M	19.7M	61.1M	0.0M
ERR5974733	147.1M	0.0M	67.0M	27.7M	0.0M	49.4M	24.7M	24.7M	24.7M	24.7M	33.3M	16.1M	49.4M	0.0M
ERR5974734	113.2M	0.0M	42.3M	20.7M	0.0M	47.4M	23.7M	23.7M	23.7M	23.7M	31.3M	16.1M	47.4M	0.0M
ERR5974735	140.3M	0.0M	54.0M	26.7M	0.0M	56.1M	28.1M	28.1M	28.1M	28.1M	37.1M	19.0M	56.1M	0.0M
ERR5974736	148.9M	0.0M	54.1M	21.1M	0.0M	70.0M	35.0M	35.0M	35.0M	35.0M	47.5M	22.6M	70.0M	0.0M
ERR5974737	128.5M	0.0M	41.4M	42.1M	0.0M	41.8M	20.9M	20.9M	20.9M	20.9M	26.8M	15.0M	41.8M	0.0M
ERR5974738	136.6M	0.0M	52.1M	25.2M	0.0M	56.2M	28.1M	28.1M	28.1M	28.1M	37.6M	18.6M	56.2M	0.0M
ERR5974739	145.4M	0.0M	53.4M	29.5M	0.0M	59.1M	29.5M	29.5M	29.5M	29.5M	40.0M	19.0M	59.1M	0.0M
ERR5974740	114.6M	0.0M	38.6M	18.2M	0.0M	54.7M	27.4M	27.4M	27.4M	27.4M	36.3M	18.4M	54.7M	0.0M
ERR5974741	148.1M	0.0M	82.2M	28.3M	0.0M	35.3M	17.7M	17.7M	17.7M	17.7M	21.4M	14.0M	35.3M	0.0M
ERR5974742	145.5M	0.0M	68.4M	28.9M	0.0M	45.2M	22.6M	22.6M	22.6M	22.6M	27.6M	17.6M	45.2M	0.0M
ERR5974743	95.6M	0.0M	46.1M	21.9M	0.0M	25.5M	12.8M	12.8M	12.8M	12.8M	14.8M	10.7M	25.5M	0.0M
ERR5974744	98.5M	0.0M	50.6M	19.6M	0.0M	26.5M	13.2M	13.2M	13.2M	13.2M	15.0M	11.4M	26.5M	0.0M
ERR5974745	120.2M	0.0M	64.2M	23.1M	0.0M	30.7M	15.4M	15.4M	15.4M	15.4M	17.9M	12.8M	30.7M	0.0M
ERR5974746	146.9M	0.0M	63.6M	24.4M	0.0M	55.6M	27.8M	27.8M	27.8M	27.8M	34.4M	21.3M	55.6M	0.0M
ERR5974747	99.9M	0.0M	64.5M	12.7M	0.0M	21.5M	10.7M	10.7M	10.7M	10.7M	13.8M	7.6M	21.5M	0.0M
ERR5974748	145.7M	0.0M	91.9M	29.3M	0.0M	22.5M	11.3M	11.3M	11.3M	11.3M	12.7M	9.8M	22.5M	0.0M
ERR5974749	152.7M	0.0M	81.8M	36.9M	0.0M	31.7M	15.8M	15.8M	15.8M	15.8M	18.1M	13.5M	31.7M	0.0M

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: rseqc_bam_stat_table

Sort	Column	Description	ID	Scale
\|\|	Total records	Total records	`total_records`	read_count
\|\|	QC failed	QC failed	`qc_failed`	read_count
\|\|	Duplicates	Optical/PCR duplicate	`optical_pcr_duplicate`	read_count
\|\|	Non primary hit	Non primary hit	`non_primary_hits`	read_count
\|\|	Unmapped	Unmapped reads	`unmapped_reads`	read_count
\|\|	Unique	mapq >= mapq_cut (unique)	`mapq_gte_mapq_cut_unique`	read_count
\|\|	Read-1	Read-1	`read_1`	read_count
\|\|	Read-2	Read-2	`read_2`	read_count
\|\|	+ve strand	Reads map to '+'	`reads_map_to_sense`	read_count
\|\|	-ve strand	Reads map to '-'	`reads_map_to_antisense`	read_count
\|\|	Non-splice reads	Non-splice reads	`non_splice_reads`	read_count
\|\|	Splice reads	Splice reads	`splice_reads`	read_count
\|\|	Proper pairs	Reads mapped in proper pairs	`reads_mapped_in_proper_pairs`	read_count
\|\|	Different chrom	Proper-paired reads map to different chrom	`proper_paired_reads_map_to_different_chrom`	read_count

Samtools

Toolkit for interacting with BAM/CRAM files.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

Percent mapped

Alignment metrics from samtools stats; mapped vs. unmapped reads vs. reads mapped with MQ0.

For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

Reads mapped with MQ0 often indicate that the reads are ambiguously mapped to multiple locations in the reference sequence. This can be due to repetitive regions in the genome, the presence of alternative contigs in the reference, or due to reads that are too short to be uniquely mapped. These reads are often filtered out in downstream analyses.

Created with MultiQC

Alignment stats

This module parses the output from samtools stats. All numbers in millions.

Created with MultiQC

Showing ⁴¹/₄₁ rows and ¹³/₁₃ columns.

Sample Name	Total sequences	Mapped & paired	Properly paired	Duplicated	QC Failed	Reads MQ0	Mapped bases (CIGAR)	Bases Trimmed	Duplicated bases	Diff chromosomes	Other orientation	Inward pairs	Outward pairs
ERR5974709	122.4M	122.4M	122.4M	67.9M	0.0M	1.8M	15982.9Mb	0.0Mb	8948.1Mb	0.0M	0.0M	44.0M	17.2M
ERR5974710	86.7M	86.7M	86.7M	38.4M	0.0M	1.1M	11157.2Mb	0.0Mb	4981.1Mb	0.0M	0.0M	31.1M	12.2M
ERR5974711	118.8M	118.8M	118.8M	62.3M	0.0M	2.7M	15181.5Mb	0.0Mb	8001.6Mb	0.0M	0.0M	41.1M	18.3M
ERR5974712	113.9M	113.9M	113.9M	0.0M	0.0M	1.5M	14094.7Mb	0.0Mb	0.0Mb	0.0M	0.0M	40.3M	16.7M
ERR5974713	87.4M	87.4M	87.4M	36.3M	0.0M	1.0M	11418.0Mb	0.0Mb	4782.4Mb	0.0M	0.0M	31.7M	12.0M
ERR5974714	80.7M	80.7M	80.7M	36.0M	0.0M	1.2M	10360.2Mb	0.0Mb	4632.4Mb	0.0M	0.0M	28.5M	11.9M
ERR5974715	116.8M	116.8M	116.8M	59.1M	0.0M	2.9M	15184.7Mb	0.0Mb	7720.8Mb	0.0M	0.0M	42.0M	16.4M
ERR5974716	95.6M	95.6M	95.6M	46.9M	0.0M	1.5M	12053.2Mb	0.0Mb	5937.7Mb	0.0M	0.0M	32.9M	14.9M
ERR5974717	87.7M	87.7M	87.7M	47.3M	0.0M	2.1M	11045.8Mb	0.0Mb	5989.2Mb	0.0M	0.0M	30.8M	13.1M
ERR5974718	100.6M	100.6M	100.6M	0.0M	0.0M	2.4M	13006.2Mb	0.0Mb	0.0Mb	0.0M	0.0M	35.4M	14.9M
ERR5974719	114.5M	114.5M	114.5M	58.8M	0.0M	2.1M	14768.4Mb	0.0Mb	7625.9Mb	0.0M	0.0M	40.3M	17.0M
ERR5974720	113.6M	113.6M	113.6M	60.5M	0.0M	1.9M	14750.7Mb	0.0Mb	7913.5Mb	0.0M	0.0M	41.1M	15.7M
ERR5974721	117.2M	117.2M	117.2M	63.7M	0.0M	2.1M	14444.7Mb	0.0Mb	7877.7Mb	0.0M	0.0M	40.0M	18.6M
ERR5974722	119.0M	119.0M	119.0M	0.0M	0.0M	3.1M	15235.2Mb	0.0Mb	0.0Mb	0.0M	0.0M	41.9M	17.6M
ERR5974723	115.4M	115.4M	115.4M	0.0M	0.0M	2.0M	14310.2Mb	0.0Mb	0.0Mb	0.0M	0.0M	39.6M	18.2M
ERR5974724	117.4M	117.4M	117.4M	93.2M	0.0M	4.5M	15026.6Mb	0.0Mb	12071.9Mb	0.0M	0.0M	41.1M	17.6M
ERR5974725	117.7M	117.7M	117.7M	55.5M	0.0M	2.1M	14923.7Mb	0.0Mb	7070.4Mb	0.0M	0.0M	40.5M	18.3M
ERR5974726	92.9M	92.9M	92.9M	37.8M	0.0M	1.3M	11888.2Mb	0.0Mb	4858.2Mb	0.0M	0.0M	33.4M	13.1M
ERR5974727	118.2M	118.2M	118.2M	0.0M	0.0M	1.9M	15262.9Mb	0.0Mb	0.0Mb	0.0M	0.0M	42.0M	17.1M
ERR5974728	80.6M	80.6M	80.6M	34.0M	0.0M	1.2M	10293.9Mb	0.0Mb	4347.6Mb	0.0M	0.0M	28.1M	12.3M
ERR5974729	114.9M	114.9M	114.9M	59.9M	0.0M	2.5M	14943.8Mb	0.0Mb	7830.5Mb	0.0M	0.0M	41.9M	15.5M
ERR5974730	114.1M	114.1M	114.1M	0.0M	0.0M	3.0M	14710.8Mb	0.0Mb	0.0Mb	0.0M	0.0M	40.3M	16.7M
ERR5974731	91.4M	91.4M	91.4M	43.3M	0.0M	2.2M	11622.7Mb	0.0Mb	5503.6Mb	0.0M	0.0M	31.6M	14.1M
ERR5974732	125.9M	125.9M	125.9M	61.1M	0.0M	2.8M	16494.6Mb	0.0Mb	8082.6Mb	0.0M	0.0M	45.3M	17.6M
ERR5974733	119.3M	119.3M	119.3M	67.0M	0.0M	2.6M	15409.8Mb	0.0Mb	8703.2Mb	0.0M	0.0M	41.8M	17.9M
ERR5974734	92.5M	92.5M	92.5M	42.3M	0.0M	1.9M	11928.2Mb	0.0Mb	5479.4Mb	0.0M	0.0M	32.7M	13.5M
ERR5974735	113.6M	113.6M	113.6M	54.0M	0.0M	2.5M	14558.2Mb	0.0Mb	6956.6Mb	0.0M	0.0M	40.3M	16.5M
ERR5974736	127.8M	127.8M	127.8M	54.1M	0.0M	1.8M	16150.1Mb	0.0Mb	6860.6Mb	0.0M	0.0M	43.7M	20.2M
ERR5974737	86.4M	86.4M	86.4M	0.0M	0.0M	5.2M	11119.9Mb	0.0Mb	0.0Mb	0.0M	0.0M	31.0M	12.2M
ERR5974738	111.5M	111.5M	111.5M	0.0M	0.0M	2.5M	14008.7Mb	0.0Mb	0.0Mb	0.0M	0.0M	37.9M	17.9M
ERR5974739	116.0M	116.0M	116.0M	0.0M	0.0M	2.9M	14895.9Mb	0.0Mb	0.0Mb	0.0M	0.0M	40.3M	17.6M
ERR5974740	96.4M	96.4M	96.4M	38.6M	0.0M	1.7M	12324.3Mb	0.0Mb	4965.9Mb	0.0M	0.0M	34.5M	13.7M
ERR5974741	119.9M	119.9M	119.9M	82.2M	0.0M	2.5M	15499.2Mb	0.0Mb	10772.4Mb	0.0M	0.0M	44.2M	15.7M
ERR5974742	116.5M	116.5M	116.5M	68.4M	0.0M	2.5M	15310.2Mb	0.0Mb	9033.6Mb	0.0M	0.0M	43.1M	15.2M
ERR5974743	73.6M	73.6M	73.6M	46.1M	0.0M	2.4M	9796.9Mb	0.0Mb	6198.6Mb	0.0M	0.0M	28.5M	8.3M
ERR5974744	78.9M	78.9M	78.9M	0.0M	0.0M	1.8M	10528.2Mb	0.0Mb	0.0Mb	0.0M	0.0M	30.7M	8.8M
ERR5974745	97.1M	97.1M	97.1M	0.0M	0.0M	2.1M	12770.9Mb	0.0Mb	0.0Mb	0.0M	0.0M	37.0M	11.6M
ERR5974746	122.5M	122.5M	122.5M	63.6M	0.0M	2.2M	15544.2Mb	0.0Mb	8108.0Mb	0.0M	0.0M	43.2M	18.1M
ERR5974747	87.2M	87.2M	87.2M	64.5M	0.0M	1.2M	10907.7Mb	0.0Mb	8163.3Mb	0.0M	0.0M	30.6M	13.0M
ERR5974748	116.4M	116.4M	116.4M	0.0M	0.0M	3.1M	15335.7Mb	0.0Mb	0.0Mb	0.0M	0.0M	44.9M	13.3M
ERR5974749	115.8M	115.8M	115.8M	81.8M	0.0M	4.0M	15138.7Mb	0.0Mb	10777.8Mb	0.0M	0.0M	42.9M	15.0M

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: samtools-stats-dp_table

Sort	Column	Description	ID	Scale
\|\|	Total sequences	Total sequences	`raw_total_sequences`	read_count
\|\|	Mapped & paired	Paired-end technology bit set + both mates mapped	`reads_mapped_and_paired`	read_count
\|\|	Properly paired	Proper-pair bit set	`reads_properly_paired`	read_count
\|\|	Duplicated	PCR or optical duplicate bit set	`reads_duplicated`	read_count
\|\|	QC Failed	QC Failed	`reads_QC_failed`	read_count
\|\|	Reads MQ0	Reads mapped and MQ=0	`reads_MQ0`	read_count
\|\|	Mapped bases (CIGAR)	Mapped bases (CIGAR)	`bases_mapped__cigar`	base_count
\|\|	Bases Trimmed	Bases Trimmed	`bases_trimmed`	base_count
\|\|	Duplicated bases	Duplicated bases	`bases_duplicated`	base_count
\|\|	Diff chromosomes	Pairs on different chromosomes	`pairs_on_different_chromosomes`	read_count
\|\|	Other orientation	Pairs with other orientation	`pairs_with_other_orientation`	read_count
\|\|	Inward pairs	Inward oriented pairs	`inward_oriented_pairs`	read_count
\|\|	Outward pairs	Outward oriented pairs	`outward_oriented_pairs`	read_count

Flagstat

This module parses the output from samtools flagstat

Created with MultiQC

Showing ⁴¹/₄₁ rows and ¹¹/₁₁ columns.

Sample Name	Total Reads	Total Passed QC	Mapped	Secondary Alignments	Duplicates	Paired in Sequencing	Properly Paired	Self and mate mapped	Singletons	Mate mapped to diff chr	Diff chr (mapQ >= 5)
ERR5974709	144.1M	144.1M	144.1M	21.7M	0.0M	122.4M	122.4M	122.4M	0.0M	0.0M	0.0M
ERR5974710	102.0M	102.0M	102.0M	15.2M	0.0M	86.7M	86.7M	86.7M	0.0M	0.0M	0.0M
ERR5974711	147.3M	147.3M	147.3M	28.5M	0.0M	118.8M	118.8M	118.8M	0.0M	0.0M	0.0M
ERR5974712	132.6M	132.6M	132.6M	18.6M	0.0M	113.9M	113.9M	113.9M	0.0M	0.0M	0.0M
ERR5974713	100.3M	100.3M	100.3M	13.0M	0.0M	87.4M	87.4M	87.4M	0.0M	0.0M	0.0M
ERR5974714	94.3M	94.3M	94.3M	13.6M	0.0M	80.7M	80.7M	80.7M	0.0M	0.0M	0.0M
ERR5974715	146.1M	146.1M	146.1M	29.2M	59.1M	116.8M	116.8M	116.8M	0.0M	0.0M	0.0M
ERR5974716	113.1M	113.1M	113.1M	17.5M	0.0M	95.6M	95.6M	95.6M	0.0M	0.0M	0.0M
ERR5974717	108.9M	108.9M	108.9M	21.2M	0.0M	87.7M	87.7M	87.7M	0.0M	0.0M	0.0M
ERR5974718	124.7M	124.7M	124.7M	24.1M	0.0M	100.6M	100.6M	100.6M	0.0M	0.0M	0.0M
ERR5974719	136.7M	136.7M	136.7M	22.2M	0.0M	114.5M	114.5M	114.5M	0.0M	0.0M	0.0M
ERR5974720	135.1M	135.1M	135.1M	21.6M	0.0M	113.6M	113.6M	113.6M	0.0M	0.0M	0.0M
ERR5974721	141.8M	141.8M	141.8M	24.5M	0.0M	117.2M	117.2M	117.2M	0.0M	0.0M	0.0M
ERR5974722	148.5M	148.5M	148.5M	29.6M	0.0M	119.0M	119.0M	119.0M	0.0M	0.0M	0.0M
ERR5974723	137.7M	137.7M	137.7M	22.3M	0.0M	115.4M	115.4M	115.4M	0.0M	0.0M	0.0M
ERR5974724	156.6M	156.6M	156.6M	39.2M	0.0M	117.4M	117.4M	117.4M	0.0M	0.0M	0.0M
ERR5974725	141.0M	141.0M	141.0M	23.3M	55.5M	117.7M	117.7M	117.7M	0.0M	0.0M	0.0M
ERR5974726	107.8M	107.8M	107.8M	14.9M	0.0M	92.9M	92.9M	92.9M	0.0M	0.0M	0.0M
ERR5974727	139.0M	139.0M	139.0M	20.8M	0.0M	118.2M	118.2M	118.2M	0.0M	0.0M	0.0M
ERR5974728	94.7M	94.7M	94.7M	14.1M	0.0M	80.6M	80.6M	80.6M	0.0M	0.0M	0.0M
ERR5974729	143.6M	143.6M	143.6M	28.8M	59.9M	114.9M	114.9M	114.9M	0.0M	0.0M	0.0M
ERR5974730	142.7M	142.7M	142.7M	28.7M	0.0M	114.1M	114.1M	114.1M	0.0M	0.0M	0.0M
ERR5974731	113.1M	113.1M	113.1M	21.7M	0.0M	91.4M	91.4M	91.4M	0.0M	0.0M	0.0M
ERR5974732	154.4M	154.4M	154.4M	28.5M	61.1M	125.9M	125.9M	125.9M	0.0M	0.0M	0.0M
ERR5974733	147.1M	147.1M	147.1M	27.7M	0.0M	119.3M	119.3M	119.3M	0.0M	0.0M	0.0M
ERR5974734	113.2M	113.2M	113.2M	20.7M	0.0M	92.5M	92.5M	92.5M	0.0M	0.0M	0.0M
ERR5974735	140.3M	140.3M	140.3M	26.7M	0.0M	113.6M	113.6M	113.6M	0.0M	0.0M	0.0M
ERR5974736	148.9M	148.9M	148.9M	21.1M	54.1M	127.8M	127.8M	127.8M	0.0M	0.0M	0.0M
ERR5974737	128.5M	128.5M	128.5M	42.1M	41.4M	86.4M	86.4M	86.4M	0.0M	0.0M	0.0M
ERR5974738	136.6M	136.6M	136.6M	25.2M	52.1M	111.5M	111.5M	111.5M	0.0M	0.0M	0.0M
ERR5974739	145.4M	145.4M	145.4M	29.5M	53.4M	116.0M	116.0M	116.0M	0.0M	0.0M	0.0M
ERR5974740	114.6M	114.6M	114.6M	18.2M	38.6M	96.4M	96.4M	96.4M	0.0M	0.0M	0.0M
ERR5974741	148.1M	148.1M	148.1M	28.3M	82.2M	119.9M	119.9M	119.9M	0.0M	0.0M	0.0M
ERR5974742	145.5M	145.5M	145.5M	28.9M	68.4M	116.5M	116.5M	116.5M	0.0M	0.0M	0.0M
ERR5974743	95.6M	95.6M	95.6M	21.9M	46.1M	73.6M	73.6M	73.6M	0.0M	0.0M	0.0M
ERR5974744	98.5M	98.5M	98.5M	19.6M	50.6M	78.9M	78.9M	78.9M	0.0M	0.0M	0.0M
ERR5974745	120.2M	120.2M	120.2M	23.1M	0.0M	97.1M	97.1M	97.1M	0.0M	0.0M	0.0M
ERR5974746	146.9M	146.9M	146.9M	24.4M	0.0M	122.5M	122.5M	122.5M	0.0M	0.0M	0.0M
ERR5974747	99.9M	99.9M	99.9M	12.7M	64.5M	87.2M	87.2M	87.2M	0.0M	0.0M	0.0M
ERR5974748	145.7M	145.7M	145.7M	29.3M	91.9M	116.4M	116.4M	116.4M	0.0M	0.0M	0.0M
ERR5974749	152.7M	152.7M	152.7M	36.9M	81.8M	115.8M	115.8M	115.8M	0.0M	0.0M	0.0M

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: samtools-flagstat-table_table

Sort	Column	Description	ID	Scale
\|\|	Total Reads	Total Reads	`flagstat_total`	read_count
\|\|	Total Passed QC	Total Passed QC	`total_passed`	read_count
\|\|	Mapped	Mapped	`mapped_passed`	read_count
\|\|	Secondary Alignments	Secondary Alignments	`secondary_passed`	read_count
\|\|	Duplicates	Duplicates	`duplicates_passed`	read_count
\|\|	Paired in Sequencing	Paired in Sequencing	`paired_in_sequencing_passed`	read_count
\|\|	Properly Paired	Properly Paired	`properly_paired_passed`	read_count
\|\|	Self and mate mapped	Reads with itself and mate mapped	`with_itself_and_mate_mapped_passed`	read_count
\|\|	Singletons	Singletons	`singletons_passed`	read_count
\|\|	Mate mapped to diff chr	Mate mapped to different chromosome	`with_mate_mapped_to_a_different_chr_passed`	read_count
\|\|	Diff chr (mapQ >= 5)	Mate mapped to different chromosome (mapQ >= 5)	`with_mate_mapped_to_a_different_chr_mapQ_5__passed`	read_count

Flagstat: Percentage of total

This module parses the output from samtools flagstat

Created with MultiQC

Showing ⁴¹/₄₁ rows and ¹¹/₁₁ columns.

Sample Name	Total Reads	Total Passed QC	Mapped	Secondary Alignments	Duplicates	Paired in Sequencing	Properly Paired	Self and mate mapped	Singletons	Mate mapped to diff chr	Diff chr (mapQ >= 5)
ERR5974709	100.0%	100.0%	100.0%	15.1%	0.0%	84.9%	84.9%	84.9%	0.0%	0.0%	0.0%
ERR5974710	100.0%	100.0%	100.0%	14.9%	0.0%	85.1%	85.1%	85.1%	0.0%	0.0%	0.0%
ERR5974711	100.0%	100.0%	100.0%	19.4%	0.0%	80.6%	80.6%	80.6%	0.0%	0.0%	0.0%
ERR5974712	100.0%	100.0%	100.0%	14.0%	0.0%	86.0%	86.0%	86.0%	0.0%	0.0%	0.0%
ERR5974713	100.0%	100.0%	100.0%	12.9%	0.0%	87.1%	87.1%	87.1%	0.0%	0.0%	0.0%
ERR5974714	100.0%	100.0%	100.0%	14.5%	0.0%	85.5%	85.5%	85.5%	0.0%	0.0%	0.0%
ERR5974715	100.0%	100.0%	100.0%	20.0%	40.5%	80.0%	80.0%	80.0%	0.0%	0.0%	0.0%
ERR5974716	100.0%	100.0%	100.0%	15.5%	0.0%	84.5%	84.5%	84.5%	0.0%	0.0%	0.0%
ERR5974717	100.0%	100.0%	100.0%	19.5%	0.0%	80.5%	80.5%	80.5%	0.0%	0.0%	0.0%
ERR5974718	100.0%	100.0%	100.0%	19.4%	0.0%	80.6%	80.6%	80.6%	0.0%	0.0%	0.0%
ERR5974719	100.0%	100.0%	100.0%	16.2%	0.0%	83.8%	83.8%	83.8%	0.0%	0.0%	0.0%
ERR5974720	100.0%	100.0%	100.0%	16.0%	0.0%	84.0%	84.0%	84.0%	0.0%	0.0%	0.0%
ERR5974721	100.0%	100.0%	100.0%	17.3%	0.0%	82.7%	82.7%	82.7%	0.0%	0.0%	0.0%
ERR5974722	100.0%	100.0%	100.0%	19.9%	0.0%	80.1%	80.1%	80.1%	0.0%	0.0%	0.0%
ERR5974723	100.0%	100.0%	100.0%	16.2%	0.0%	83.8%	83.8%	83.8%	0.0%	0.0%	0.0%
ERR5974724	100.0%	100.0%	100.0%	25.0%	0.0%	75.0%	75.0%	75.0%	0.0%	0.0%	0.0%
ERR5974725	100.0%	100.0%	100.0%	16.5%	39.3%	83.5%	83.5%	83.5%	0.0%	0.0%	0.0%
ERR5974726	100.0%	100.0%	100.0%	13.8%	0.0%	86.2%	86.2%	86.2%	0.0%	0.0%	0.0%
ERR5974727	100.0%	100.0%	100.0%	15.0%	0.0%	85.0%	85.0%	85.0%	0.0%	0.0%	0.0%
ERR5974728	100.0%	100.0%	100.0%	14.9%	0.0%	85.1%	85.1%	85.1%	0.0%	0.0%	0.0%
ERR5974729	100.0%	100.0%	100.0%	20.0%	41.7%	80.0%	80.0%	80.0%	0.0%	0.0%	0.0%
ERR5974730	100.0%	100.0%	100.0%	20.1%	0.0%	79.9%	79.9%	79.9%	0.0%	0.0%	0.0%
ERR5974731	100.0%	100.0%	100.0%	19.2%	0.0%	80.8%	80.8%	80.8%	0.0%	0.0%	0.0%
ERR5974732	100.0%	100.0%	100.0%	18.5%	39.6%	81.5%	81.5%	81.5%	0.0%	0.0%	0.0%
ERR5974733	100.0%	100.0%	100.0%	18.9%	0.0%	81.1%	81.1%	81.1%	0.0%	0.0%	0.0%
ERR5974734	100.0%	100.0%	100.0%	18.3%	0.0%	81.7%	81.7%	81.7%	0.0%	0.0%	0.0%
ERR5974735	100.0%	100.0%	100.0%	19.0%	0.0%	81.0%	81.0%	81.0%	0.0%	0.0%	0.0%
ERR5974736	100.0%	100.0%	100.0%	14.2%	36.3%	85.8%	85.8%	85.8%	0.0%	0.0%	0.0%
ERR5974737	100.0%	100.0%	100.0%	32.8%	32.2%	67.2%	67.2%	67.2%	0.0%	0.0%	0.0%
ERR5974738	100.0%	100.0%	100.0%	18.4%	38.2%	81.6%	81.6%	81.6%	0.0%	0.0%	0.0%
ERR5974739	100.0%	100.0%	100.0%	20.3%	36.7%	79.7%	79.7%	79.7%	0.0%	0.0%	0.0%
ERR5974740	100.0%	100.0%	100.0%	15.9%	33.7%	84.1%	84.1%	84.1%	0.0%	0.0%	0.0%
ERR5974741	100.0%	100.0%	100.0%	19.1%	55.5%	80.9%	80.9%	80.9%	0.0%	0.0%	0.0%
ERR5974742	100.0%	100.0%	100.0%	19.9%	47.0%	80.1%	80.1%	80.1%	0.0%	0.0%	0.0%
ERR5974743	100.0%	100.0%	100.0%	23.0%	48.2%	77.0%	77.0%	77.0%	0.0%	0.0%	0.0%
ERR5974744	100.0%	100.0%	100.0%	19.9%	51.4%	80.1%	80.1%	80.1%	0.0%	0.0%	0.0%
ERR5974745	100.0%	100.0%	100.0%	19.2%	0.0%	80.8%	80.8%	80.8%	0.0%	0.0%	0.0%
ERR5974746	100.0%	100.0%	100.0%	16.6%	0.0%	83.4%	83.4%	83.4%	0.0%	0.0%	0.0%
ERR5974747	100.0%	100.0%	100.0%	12.7%	64.5%	87.3%	87.3%	87.3%	0.0%	0.0%	0.0%
ERR5974748	100.0%	100.0%	100.0%	20.1%	63.1%	79.9%	79.9%	79.9%	0.0%	0.0%	0.0%
ERR5974749	100.0%	100.0%	100.0%	24.2%	53.6%	75.8%	75.8%	75.8%	0.0%	0.0%	0.0%

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: samtools-flagstat-pct-table_table

Sort	Column	Description	ID
\|\|	Total Reads	Total Reads	`flagstat_total_pct`
\|\|	Total Passed QC	Total Passed QC	`total_passed_pct`
\|\|	Mapped	Mapped	`mapped_passed_pct`
\|\|	Secondary Alignments	Secondary Alignments	`secondary_passed_pct`
\|\|	Duplicates	Duplicates	`duplicates_passed_pct`
\|\|	Paired in Sequencing	Paired in Sequencing	`paired_in_sequencing_passed_pct`
\|\|	Properly Paired	Properly Paired	`properly_paired_passed_pct`
\|\|	Self and mate mapped	Self and mate mapped	`with_itself_and_mate_mapped_passed_pct`
\|\|	Singletons	Singletons	`singletons_passed_pct`
\|\|	Mate mapped to diff chr	Mate mapped to diff chr	`with_mate_mapped_to_a_different_chr_passed_pct`
\|\|	Diff chr (mapQ >= 5)	Diff chr (mapQ >= 5)	`with_mate_mapped_to_a_different_chr_mapQ_5__passed_pct`

XY counts

Created with MultiQC

Mapped reads per contig

The samtools idxstats tool counts the number of mapped reads per chromosome / contig. Chromosomes with < 0.1% of the total aligned reads are omitted from this plot.

Created with MultiQC

STAR

Universal RNA-seq aligner.URL: https://github.com/alexdobin/STARDOI: 10.1093/bioinformatics/bts635

Summary Statistics

Summary statistics from the STAR alignment

Showing ⁴¹/₄₁ rows and ¹⁰/₁₉ columns.

Sample Name	Total reads	Aligned	Aligned	Uniq aligned	Uniq aligned	Multimapped	Avg. read len	Avg. mapped len	Splices	Annotated splices	GT/AG splices	GC/AG splices	AT/AC splices	Non-canonical splices	Mismatch rate	Del rate	Del len	Ins rate	Ins len
ERR5974709	64.0M	61.2M	95.6%	56.6M	88.4%	4.6M	263.0bp	261.4bp	48.0M	47.9M	47.5M	0.4M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974710	45.6M	43.4M	95.0%	39.8M	87.1%	3.6M	260.0bp	257.7bp	31.5M	31.5M	31.1M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974711	62.4M	59.4M	95.2%	54.2M	86.9%	5.2M	258.0bp	255.8bp	46.7M	46.6M	46.2M	0.3M	0.0M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.6bp
ERR5974712	59.7M	57.0M	95.4%	52.9M	88.5%	4.1M	250.0bp	248.1bp	43.1M	43.0M	42.6M	0.4M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974713	45.5M	43.7M	96.1%	40.7M	89.6%	2.9M	264.0bp	261.9bp	33.0M	32.9M	32.6M	0.3M	0.0M	0.0M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974714	42.0M	40.3M	96.0%	37.6M	89.5%	2.7M	259.0bp	257.2bp	28.7M	28.6M	28.4M	0.2M	0.0M	0.0M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974715	61.3M	58.4M	95.3%	53.3M	86.9%	5.2M	262.0bp	260.2bp	48.1M	48.0M	47.5M	0.4M	0.0M	0.1M	0.4%	0.0%	1.9bp	0.0%	1.6bp
ERR5974716	50.1M	47.8M	95.4%	44.3M	88.5%	3.5M	254.0bp	252.6bp	37.5M	37.5M	37.1M	0.3M	0.0M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.6bp
ERR5974717	45.8M	43.8M	95.7%	40.3M	88.0%	3.5M	254.0bp	252.3bp	34.8M	34.8M	34.4M	0.3M	0.0M	0.0M	0.3%	0.0%	1.8bp	0.0%	1.5bp
ERR5974718	52.4M	50.3M	96.1%	46.1M	88.0%	4.2M	260.0bp	258.7bp	42.5M	42.5M	42.0M	0.5M	0.0M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.5bp
ERR5974719	59.7M	57.3M	95.9%	53.0M	88.8%	4.2M	260.0bp	258.3bp	46.8M	46.7M	46.3M	0.4M	0.0M	0.1M	0.3%	0.0%	1.9bp	0.0%	1.6bp
ERR5974720	59.7M	56.8M	95.1%	52.6M	88.0%	4.2M	262.0bp	260.2bp	45.6M	45.5M	45.0M	0.4M	0.0M	0.1M	0.3%	0.0%	2.0bp	0.0%	1.6bp
ERR5974721	61.6M	58.6M	95.2%	53.8M	87.3%	4.8M	248.0bp	246.8bp	45.9M	45.8M	45.4M	0.4M	0.1M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.6bp
ERR5974722	62.7M	59.5M	94.8%	54.6M	87.0%	4.9M	259.0bp	256.5bp	47.0M	46.9M	46.5M	0.4M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974723	60.6M	57.7M	95.2%	53.4M	88.0%	4.4M	250.0bp	248.4bp	44.4M	44.3M	43.9M	0.3M	0.0M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.7bp
ERR5974724	61.4M	58.7M	95.6%	53.2M	86.6%	5.5M	258.0bp	256.2bp	43.5M	43.4M	43.0M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974725	61.2M	58.9M	96.1%	54.5M	89.0%	4.3M	256.0bp	253.9bp	46.8M	46.7M	46.4M	0.4M	0.0M	0.1M	0.3%	0.0%	2.1bp	0.0%	1.6bp
ERR5974726	48.0M	46.5M	96.7%	43.5M	90.5%	3.0M	258.0bp	256.5bp	35.7M	35.6M	35.3M	0.3M	0.0M	0.0M	0.3%	0.0%	2.0bp	0.0%	1.6bp
ERR5974727	61.7M	59.1M	95.8%	55.1M	89.3%	4.0M	260.0bp	258.4bp	49.0M	48.9M	48.5M	0.4M	0.0M	0.1M	0.3%	0.0%	1.9bp	0.0%	1.5bp
ERR5974728	41.9M	40.3M	96.3%	37.6M	89.8%	2.7M	257.0bp	255.8bp	32.2M	32.2M	31.9M	0.2M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974729	60.2M	57.4M	95.3%	51.9M	86.1%	5.6M	262.0bp	260.4bp	46.6M	46.5M	46.1M	0.3M	0.0M	0.1M	0.3%	0.0%	1.7bp	0.0%	1.7bp
ERR5974730	59.7M	57.0M	95.5%	52.3M	87.5%	4.8M	260.0bp	258.3bp	43.4M	43.4M	43.1M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974731	47.5M	45.7M	96.2%	42.1M	88.6%	3.6M	256.0bp	254.6bp	35.7M	35.6M	35.4M	0.2M	0.0M	0.0M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974732	66.3M	62.9M	95.0%	57.7M	87.1%	5.2M	264.0bp	262.4bp	48.2M	48.1M	47.7M	0.4M	0.0M	0.1M	0.3%	0.0%	1.7bp	0.0%	1.7bp
ERR5974733	62.2M	59.7M	96.0%	54.7M	88.0%	5.0M	260.0bp	258.4bp	47.5M	47.4M	47.1M	0.3M	0.0M	0.1M	0.3%	0.0%	2.2bp	0.0%	1.6bp
ERR5974734	48.3M	46.2M	95.7%	42.5M	87.8%	3.8M	259.0bp	258.3bp	36.0M	36.0M	35.7M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974735	59.6M	56.8M	95.3%	52.0M	87.2%	4.8M	258.0bp	256.6bp	45.1M	45.0M	44.7M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974736	66.3M	63.9M	96.4%	59.6M	90.0%	4.3M	255.0bp	253.2bp	48.5M	48.4M	48.0M	0.4M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974737	45.2M	43.2M	95.7%	38.4M	85.0%	4.8M	259.0bp	257.7bp	35.1M	35.1M	34.8M	0.3M	0.0M	0.0M	0.3%	0.0%	2.0bp	0.0%	1.6bp
ERR5974738	57.9M	55.7M	96.2%	51.5M	89.0%	4.2M	253.0bp	251.7bp	42.7M	42.6M	42.3M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974739	61.0M	58.0M	95.1%	52.8M	86.7%	5.1M	259.0bp	257.2bp	43.6M	43.5M	43.1M	0.4M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974740	50.4M	48.2M	95.6%	44.8M	89.0%	3.4M	258.0bp	256.2bp	37.2M	37.2M	36.7M	0.4M	0.0M	0.1M	0.3%	0.0%	2.0bp	0.0%	1.7bp
ERR5974741	62.9M	59.9M	95.3%	54.7M	86.9%	5.3M	260.0bp	259.1bp	51.9M	51.8M	51.4M	0.3M	0.0M	0.1M	0.3%	0.0%	1.8bp	0.0%	1.6bp
ERR5974742	61.5M	58.3M	94.7%	52.7M	85.6%	5.6M	265.0bp	263.1bp	51.3M	51.3M	50.9M	0.3M	0.0M	0.1M	0.3%	0.0%	1.7bp	0.0%	1.6bp
ERR5974743	38.5M	36.8M	95.7%	33.4M	86.9%	3.4M	268.0bp	266.9bp	33.2M	33.2M	32.9M	0.2M	0.0M	0.1M	0.3%	0.0%	1.7bp	0.0%	1.7bp
ERR5974744	41.0M	39.5M	96.2%	35.8M	87.2%	3.7M	268.0bp	267.1bp	37.5M	37.4M	37.1M	0.2M	0.0M	0.1M	0.3%	0.0%	2.5bp	0.0%	1.7bp
ERR5974745	50.7M	48.5M	95.8%	44.2M	87.2%	4.4M	265.0bp	263.5bp	43.1M	43.0M	42.7M	0.3M	0.0M	0.1M	0.3%	0.0%	1.9bp	0.0%	1.6bp
ERR5974746	63.8M	61.2M	95.9%	56.5M	88.6%	4.7M	256.0bp	254.4bp	53.0M	53.0M	52.5M	0.4M	0.0M	0.1M	0.3%	0.0%	2.0bp	0.0%	1.6bp
ERR5974747	44.8M	43.6M	97.3%	41.1M	91.8%	2.5M	252.0bp	251.0bp	36.6M	36.5M	36.3M	0.2M	0.0M	0.0M	0.3%	0.0%	1.9bp	0.0%	1.6bp
ERR5974748	60.4M	58.2M	96.3%	53.4M	88.4%	4.8M	266.0bp	264.6bp	62.0M	62.0M	61.6M	0.4M	0.0M	0.1M	0.3%	0.0%	1.7bp	0.0%	1.6bp
ERR5974749	60.5M	57.9M	95.7%	52.3M	86.4%	5.6M	263.0bp	261.8bp	54.4M	54.3M	53.9M	0.3M	0.0M	0.1M	0.3%	0.0%	2.0bp	0.0%	1.8bp

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order. Table ID: star_summary_table_table

Sort	Column	Description	ID	Scale
\|\|	Total reads	Number of input reads	`star-total_reads`	read_count
\|\|	Aligned	Mapped reads	`star-mapped`	read_count
\|\|	Aligned	% Mapped reads	`star-mapped_percent`
\|\|	Uniq aligned	Uniquely mapped reads	`star-uniquely_mapped`	read_count
\|\|	Uniq aligned	% Uniquely mapped reads	`star-uniquely_mapped_percent`
\|\|	Multimapped	Multiple mapped reads	`star-multimapped`	read_count
\|\|	Avg. read len	Average input read length	`star-avg_input_read_length`
\|\|	Avg. mapped len	Average mapped length	`star-avg_mapped_read_length`
\|\|	Splices	Number of splices: Total	`star-num_splices`	read_count
\|\|	Annotated splices	Number of splices: Annotated (sjdb)	`star-num_annotated_splices`	read_count
\|\|	GT/AG splices	Number of splices: GT/AG	`star-num_GTAG_splices`	read_count
\|\|	GC/AG splices	Number of splices: GC/AG	`star-num_GCAG_splices`	read_count
\|\|	AT/AC splices	Number of splices: AT/AC	`star-num_ATAC_splices`	read_count
\|\|	Non-canonical splices	Number of splices: Non-canonical	`star-num_noncanonical_splices`	read_count
\|\|	Mismatch rate	Mismatch rate per base	`star-mismatch_rate`
\|\|	Del rate	Deletion rate per base	`star-deletion_rate`
\|\|	Del len	Deletion average length	`star-deletion_length`
\|\|	Ins rate	Insertion rate per base	`star-insertion_rate`
\|\|	Ins len	Insertion average length	`star-insertion_length`

Alignment Scores

Created with MultiQC

Sample relationships

Plots interrogating sample relationships, based on final count matrices.

STAR_SALMON DESeq2 sample similarity

is generated from clustering by Euclidean distances between DESeq2 rlog values for each sample in the deseq2_qc.r script.

Created with MultiQC

STAR_SALMON DESeq2 PCA plot

PCA plot between samples in the experiment. These values are calculated using DESeq2 in the deseq2_qc.r script.

Created with MultiQC

Biotype Counts

Biotype Counts shows reads overlapping genomic features of different biotypes, counted by featureCounts.

Created with MultiQC

Software Versions

Software Versions lists versions of software tools extracted from file contents.

Group	Software	Version
BEDTOOLS_GENOMECOV_FW	bedtools	`2.31.1`
CUSTOM_GETCHROMSIZES	getchromsizes	`1.21`
CUSTOM_TX2GENE	python	`3.10.4`
DESEQ2_QC_STAR_SALMON	bioconductor-deseq2	`1.28.0`
	r-base	`4.0.3`
DupRadar	bioconductor-dupradar	`1.32.0`
FASTQC_RAW	fastqc	`0.12.1`
FASTQC_TRIM	fastqc	`0.12.1`
FQ_LINT	fq	`0.12.0 (2024-07-08)`
FQ_SUBSAMPLE	fq	`0.12.0 (2024-07-08)`
GTF2BED	perl	`5.26.2`
GTF_FILTER	python	`3.9.5`
GUNZIP_FASTA	gunzip	`1.13`
GUNZIP_GTF	gunzip	`1.13`
MAKE_TRANSCRIPTS_FASTA	rsem	`1.3.1`
	star	`2.7.10a`
MULTIQC_CUSTOM_BIOTYPE	python	`3.9.5`
PICARD_MARKDUPLICATES	picard	`3.1.1`
QUALIMAP_RNASEQ	qualimap	`2.3`
RSEQC_BAMSTAT	rseqc	`5.0.2`
RSEQC_INFEREXPERIMENT	rseqc	`5.0.2`
RSEQC_INNERDISTANCE	rseqc	`5.0.2`
RSEQC_JUNCTIONANNOTATION	rseqc	`5.0.2`
RSEQC_JUNCTIONSATURATION	rseqc	`5.0.2`
RSEQC_READDISTRIBUTION	rseqc	`5.0.2`
RSEQC_READDUPLICATION	rseqc	`5.0.2`
SALMON_INDEX	salmon	`1.10.3`
SALMON_QUANT	salmon	`1.10.3`
SAMTOOLS_FLAGSTAT	samtools	`1.21`
SAMTOOLS_IDXSTATS	samtools	`1.21`
SAMTOOLS_INDEX	samtools	`1.21`
SAMTOOLS_SORT	samtools	`1.21`
SAMTOOLS_STATS	samtools	`1.21`
SE_GENE_UNIFIED	bioconductor-summarizedexperiment	`1.32.0`
SE_TRANSCRIPT_UNIFIED	bioconductor-summarizedexperiment	`1.32.0`
STAR_ALIGN	gawk	`5.1.0`
	samtools	`1.21`
	star	`2.7.11b`
STAR_GENOMEGENERATE	gawk	`5.1.0`
	samtools	`1.21`
	star	`2.7.11b`
STRINGTIE_STRINGTIE	stringtie	`2.2.3`
SUBREAD_FEATURECOUNTS	subread	`2.0.6`
TXIMETA_TXIMPORT	bioconductor-tximeta	`1.20.1`
UCSC_BEDCLIP	ucsc	`377`
UCSC_BEDGRAPHTOBIGWIG	ucsc	`469`
Workflow	Nextflow	`25.04.6`
	nf-core/rnaseq	`v3.20.0-gb971ba1`
fastp	fastp	`0.24.0`

nf-core/rnaseq Methods Description

Suggested text and references to use when describing pipeline usage within the methods section of a publication.URL: https://github.com/nf-core/rnaseq

Methods

Data was processed using nf-core/rnaseq v3.20.0 (doi: 10.5281/zenodo.1400710) of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

The pipeline was executed with Nextflow v25.04.6 (Di Tommaso et al., 2017) with the following command:

nextflow run nf-core/rnaseq -r 3.20.0 -profile singularity -with-tower -resume --input ./samplesheet.csv --outdir ../results --gencode true --fasta ../../genomes/GRCh38.primary_assembly.genome.fa.gz --gtf ../../genomes/gencode.v43.annotation.gtf.gz --trimmer fastp --skip_pseudo_alignment --aligner star_salmon

References

Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. doi: 10.1038/nbt.3820
Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. doi: 10.1038/s41587-020-0439-x
Grüning, B., Dale, R., Sjödin, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Köster, J., & Bioconda Team. (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7
da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics (Oxford, England), 33(16), 2580–2582. doi: 10.1093/bioinformatics/btx192

Notes:

The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!
You should also cite all software used within this run. Check the "Software Versions" of this report to get version information.

nf-core/rnaseq Workflow Summary

this information is collected when the pipeline is started.URL: https://github.com/nf-core/rnaseq

Input/output options

input: ./samplesheet.csv
outdir: ../results

Reference genome options

fasta: ../../genomes/GRCh38.primary_assembly.genome.fa.gz
gencode: true
gtf: ../../genomes/gencode.v43.annotation.gtf.gz

Read trimming options

trimmer: fastp

Process skipping options

skip_pseudo_alignment: true

Generic options

trace_report_suffix: 2025-09-04_08-42-10

Core Nextflow options

configFiles: /home/gmdazevedo/.nextflow/config, /home/gmdazevedo/.nextflow/assets/nf-core/rnaseq/nextflow.config
containerEngine: singularity
launchDir: /mnt/beegfs/scratch/gmdazevedo/rstudio/sjogren_rnaseq/ERP129369/assets
profile: singularity
projectDir: /home/gmdazevedo/.nextflow/assets/nf-core/rnaseq
revision: 3.20.0
runName: marvelous_leibniz
userName: gmdazevedo
workDir: /mnt/beegfs/scratch/gmdazevedo/rstudio/sjogren_rnaseq/ERP129369/assets/work

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